Journal articles: 'Metric quality assessment'

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Kwan, Chiman, and Bence Budavari. "A New Blind Video Quality Metric for Assessing Different Turbulence Mitigation Algorithms." Electronics 10, no. 18 (September 16, 2021): 2277. http://dx.doi.org/10.3390/electronics10182277.

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Although many algorithms have been proposed to mitigate air turbulence in optical videos, there do not seem to be consistent blind video quality assessment metrics that can reliably assess different approaches. Blind video quality assessment metrics are necessary because many videos containing air turbulence do not have ground truth. In this paper, a simple and intuitive blind video quality assessment metric is proposed. This metric can reliably and consistently assess various turbulent mitigation algorithms for optical videos. Experimental results using more than 10 videos in the literature show that the proposed metrics correlate well with human subjective evaluations. Compared with an existing blind video metric and two other blind image quality metrics, the proposed metrics performed consistently better.

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Bogatyrev, Evgeney Nikolaevich, Ivan Andreevich Molodetskikh, Dmitriy Sergeevich Vatolin, and Vladimir Alexandrovich Galaktionov. "Compressed Video Quality Assessment for Super-Resolution: A Benchmark and a Quality Metric." Keldysh Institute Preprints, no. 81 (2022): 1–24. http://dx.doi.org/10.20948/prepr-2022-81.

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We developed a super-resolution (SR) benchmark to analyze SR capabilities to upscale compressed videos. The dataset for the benchmark was collected using video codecs of 5 different compression standards. We assessed 17 state-of-the-art SR models using our benchmark and evaluated their ability to preserve scene context and their robustness to compression artifacts. To get an accurate perceptual ranking of SR models, we conducted a crowd-sourced side-by-side comparison of SR results. We also analyzed the results of the benchmark and developed an objective quality assessment metric based on existing best-performing objective metrics. Our metric outperforms other video quality metrics by Spearman correlation with subjective scores for the task of upscaling compressed videos.

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RAMAN KUMAR, Umamaheswaran, Inge COUDRON, Steven PUTTEMANS, and Patrick VANDEWALLE. "Quality assessment for 3D reconstruction of building interiors." Electronic Imaging 2020, no. 17 (January 26, 2020): 36–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.17.3dmp-036.

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Applications ranging from simple visualization to complex design require 3D models of indoor environments. This has given rise to advancements in the field of automated reconstruction of such models. In this paper, we review several state-of-the-art metrics proposed for geometric comparison of 3D models of building interiors. We evaluate their performance on a real-world dataset and propose one tailored metric which can be used to assess the quality of the reconstructed model. In addition, the proposed metric can also be easily visualized to highlight the regions or structures where the reconstruction failed. To demonstrate the versatility of the proposed metric we conducted experiments on various interior models by comparison with ground truth data created by expert Blender artists. The results of the experiments were then used to improve the reconstruction pipeline.

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Aghapour Maleki, Shiva, Hassan Ghassemian, and Maryam Imani. "Spectrum Similarity-Based Quality Assessment Metric." International Journal of Information and Communication Technology Research 14, no. 4 (December 1, 2022): 19–27. http://dx.doi.org/10.52547/itrc.14.4.19.

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Ukommi, U. S. "Review of multimedia communication quality assessment techniques." Nigerian Journal of Technology 41, no. 2 (June 2, 2022): 330–38. http://dx.doi.org/10.4314/njt.v41i2.15.

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Communication pattern is drifting from conventional audio to multimedia applications, streaming live and on-demand digital video contents over telecommunications and broadcasting networks. Currently, some businesses deploy video in promoting products in a far more enriching, entertainment and informative approach than typical traditional audio would allow. However, users of multimedia applications are interested in paying for a good acceptable video quality. Thus, this paper reviews methods used in Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Metric (SSIM) and Video Quality Metric (VQM) with the objective of providing useful information to wireless video services providers in assessing and monitoring of quality of multimedia services delivered to users. Experimental comparison of PSNR, SSIM and VQM assessment methods to examine their performances in evaluation of multimedia applications has been performed. Comparing the quality performance of PSNR, SSIM and VQM metrics for Akiyo and Crew standard test sequences, it has been observed that the quality performance of the metrics improves when the bitrates allocation increase. For the test of consistency and quality performance of the metrics, observation shows that for a given bitrates of 3.84Mb/s, under CABA test configuration, Akiyo test sequence, experienced better quality performance of 46.63dB (PSNR), 99.10% (SSIM) and 11.00% (VQM) compared to lower quality performance of 36.18dB (PSNR), 90.40% (SSIM) and 22.00% (VQM) experienced by Crew test sequence. Experimental results of the media quality metrics for Akiyo and Crew standard test sequences with different temporal activity levels show that the quality performance of media content also depends on the temporal activity of the media content. The experimental results further show consistency in quality performance of PSNR, SSIM and VQM metrics for CABA and UBA test configurations. Thus, the objective metrics can be harnessed for evaluation of quality performance of multimedia applications at different channel conditions.

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Bouida, Ahmed, Mustapha Khelifi, Mohammed Beladgham, and Fatima-Zohra Hamlili. "Monte Carlo Optimization of a Combined Image Quality Assessment for Compressed Images Evaluation." Traitement du Signal 38, no. 2 (April 30, 2021): 281–89. http://dx.doi.org/10.18280/ts.380204.

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In image processing, using compression is very important in various applications, especially those using data quantities in transmission and storing. This importance becomes most required with the evolution of image quantities and the big data systems explosion. The image compression allows reducing the required binary volume of image data by encoding the image for transmission goal or database saving. The principal problem with image compression when reducing its size is the degradation that enters the image. This degradation can affect the quality of use of the compressed image. To evaluate and qualify this quality, we investigate the use of textural combined image quality metrics (TCQ) based on the fusion of full reference structural, textural, and edge evaluation metrics. To optimize this metric, we use the Monte Carlo optimization method. This approach allows us to qualify our compressed images and propose the best metric that evaluates compressed images according to several textural quality aspects.

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Torres Vega, Maria, Vittorio Sguazzo, Decebal Constantin Mocanu, and Antonio Liotta. "An experimental survey of no-reference video quality assessment methods." International Journal of Pervasive Computing and Communications 12, no. 1 (April 4, 2016): 66–86. http://dx.doi.org/10.1108/ijpcc-01-2016-0008.

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Purpose The Video Quality Metric (VQM) is one of the most used objective methods to assess video quality, because of its high correlation with the human visual system (HVS). VQM is, however, not viable in real-time deployments such as mobile streaming, not only due to its high computational demands but also because, as a Full Reference (FR) metric, it requires both the original video and its impaired counterpart. In contrast, No Reference (NR) objective algorithms operate directly on the impaired video and are considerably faster but loose out in accuracy. The purpose of this paper is to study how differently NR metrics perform in the presence of network impairments. Design/methodology/approach The authors assess eight NR metrics, alongside a lightweight FR metric, using VQM as benchmark in a self-developed network-impaired video data set. This paper covers a range of methods, a diverse set of video types and encoding conditions and a variety of network impairment test-cases. Findings The authors show the extent by which packet loss affects different video types, correlating the accuracy of NR metrics to the FR benchmark. This paper helps identifying the conditions under which simple metrics may be used effectively and indicates an avenue to control the quality of streaming systems. Originality/value Most studies in literature have focused on assessing streams that are either unaffected by the network (e.g. looking at the effects of video compression algorithms) or are affected by synthetic network impairments (i.e. via simulated network conditions). The authors show that when streams are affected by real network conditions, assessing Quality of Experience becomes even harder, as the existing metrics perform poorly.

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Sabbani, Sarachyuth, Kiran Kumar Reddi, and S. V. Achuta Rao. "Software Quality: Issues, Concerns and New Directions." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 8 (November 27, 2013): 2887–94. http://dx.doi.org/10.24297/ijct.v11i8.3007.

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Software metrics and quality models have a very important role to play in measurement of software quality. A number of well-known quality models and software metrics are used to build quality software both in industry and in academia. Development of software metrics is an ongoing process with new metrics being continuously tried out.Â However, during our research on measuring software quality using object oriented design patterns, we faced many issues related to existing software metrics and quality models. For a particular situation of interest, any established metric can be used. If none is found to be appropriate, a new metric can be devised. In this paper, we discuss some of these issues and present our approach to software quality assessment.

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Zhu, Zhe, Hantao Liu, Jiaming Lu, and Shi-Min Hu. "A Metric for Video Blending Quality Assessment." IEEE Transactions on Image Processing 29 (2020): 3014–22. http://dx.doi.org/10.1109/tip.2019.2955294.

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Botia Valderrama, Diego José Luis, and Natalia Gaviria Gómez. "Nonintrusive Method Based on Neural Networks for Video Quality of Experience Assessment." Advances in Multimedia 2016 (2016): 1–17. http://dx.doi.org/10.1155/2016/1730814.

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The measurement and evaluation of the QoE (Quality of Experience) have become one of the main focuses in the telecommunications to provide services with the expected quality for their users. However, factors like the network parameters and codification can affect the quality of video, limiting the correlation between the objective and subjective metrics. The above increases the complexity to evaluate the real quality of video perceived by users. In this paper, a model based on artificial neural networks such as BPNNs (Backpropagation Neural Networks) and the RNNs (Random Neural Networks) is applied to evaluate the subjective quality metrics MOS (Mean Opinion Score) and the PSNR (Peak Signal Noise Ratio), SSIM (Structural Similarity Index Metric), VQM (Video Quality Metric), and QIBF (Quality Index Based Frame). The proposed model allows establishing the QoS (Quality of Service) based in the strategyDiffserv. The metrics were analyzed through Pearson’s and Spearman’s correlation coefficients, RMSE (Root Mean Square Error), and outliers rate. Correlation values greater than 90% were obtained for all the evaluated metrics.

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Okarma, Krzysztof. "Current Trends and Advances in Image Quality Assessment." Elektronika ir Elektrotechnika 25, no. 3 (June 25, 2019): 77–84. http://dx.doi.org/10.5755/j01.eie.25.3.23681.

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Image quality assessment (IQA) is one of the constantly active areas of research in computer vision. Starting from the idea of Universal Image Quality Index (UIQI), followed by well-known Structural Similarity (SSIM) and its numerous extensions and modifications, through Feature Similarity (FSIM) towards combined metrics using the multi-metric fusion approach, the development of image quality assessment is still in progress. Nevertheless, regardless of new databases and the potential use of deep learning methods, some challenges remain still up to date. Some of the IQA metrics can also be used efficiently for alternative purposes, such as texture similarity estimation, quality evaluation of 3D images and 3D printed surfaces as well as video quality assessment.

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Karev, Svyatoslav V., Aleksandr A. Koshechkin, Damir A. Murzagulov, Vladimir S. Andryushchenko, and Aleksandr V. Zamyatin. "AN APPROACH TO EVALUATE THE QUALITY OF ANOMALY DETECTION IN TECHNOLOGICAL SIGNALS." Автоматизация процессов управления 2, no. 68 (2022): 80–89. http://dx.doi.org/10.35752/1991-2927-2022-2-68-80-89.

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A technological signal is a one-dimensional time series, which is an ordered sequence of discrete-time data. Due to the presence of time dimension, methods for detecting anomalies in time series should take into account time correlations and other time-related features. As a rule, the inaccuracy matrix and metrics derived from it, such as accuracy, completeness, F-measure, etc., are used to assess the quality of the anomaly detection method. These metrics, however, do not take into account the presence of time dimension. The metric, composed of the F-measure and distance-based metrics, allows you to take into account the moment of the beginning of the anomaly, the balance between errors of the first and second kind, the presence of an anomalous site. The paper proposes an approach to the construction of a quality metric for detecting anomalies in technological signals that comprehensively components these characteristics. Due to this arrangement, the metric evaluates the time dimension of the data, allows for a more adequate assessment of the presence of point anomalies and the occurrence of abnormal areas in technological signals, taking into account their characteristics, separating them from regular (normal, typical) signals. The integral assessment takes into account not only various features of the data, but can also be configured taking into account the specifics of a specific task. The paper presents the results of testing the proposed quality metric, which showed the effectiveness of the proposed approach to assessing the quality of anomaly detection in technological signals. The superiority of the proposed metric in the considered situations was on average more than 10%. At the same time, an additional key advantage of the metric over its analogues is the ability to configure it taking into account the specifics of the data and the models used for detecting anomalies.

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Yang, Jie, Jian Xiong, Guan Gui, Rongfang Song, Wang Luo, and Xianzhong Long. "Hierarchical Gradient Similarity Based Video Quality Assessment Metric." Algorithms 10, no. 3 (June 23, 2017): 72. http://dx.doi.org/10.3390/a10030072.

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Yu, Jianping, Gang Li, Shaohui Wang, and Ling Lin. "Image quality assessment metric for frame accumulated image." Review of Scientific Instruments 89, no. 1 (January 2018): 013703. http://dx.doi.org/10.1063/1.5020715.

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Bagade, Jayashri V., Kulbir Singh, and Y. H. Dandawate. "No-reference image quality assessment using fusion metric." Multimedia Tools and Applications 79, no. 3-4 (November 15, 2019): 2109–25. http://dx.doi.org/10.1007/s11042-019-08217-5.

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Tang, Liangzhi, Qingbo Wu, Wei Li, and Yinan Liu. "Deep Saliency Quality Assessment Network With Joint Metric." IEEE Access 6 (2018): 913–24. http://dx.doi.org/10.1109/access.2017.2776344.

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Ozcinar, Cagri, and Aakanksha Rana. "Quality Assessment of Super-Resolved Omnidirectional Image Quality Using Tangential Views." Electronic Imaging 2021, no. 9 (January 18, 2021): 295–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.9.iqsp-295.

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Omnidirectional images (ODIs), also known as 360-degree images, enable viewers to explore all directions of a given 360-degree scene from a fixed point. Designing an immersive imaging system with ODI is challenging as such systems require very large resolution coverage of the entire 360 viewing space to provide an enhanced quality of experience (QoE). Despite remarkable progress on single image super-resolution (SISR) methods with deep-learning techniques, no study for quality assessments of super-resolved ODIs exists to analyze the quality of such SISR techniques. This paper proposes an objective, full-reference quality assessment framework which studies quality measurement for ODIs generated by GAN-based and CNN-based SISR methods. The quality assessment framework offers to utilize tangential views to cope with the spherical nature of a given ODIs. The generated tangential views are distortion-free and can be efficiently scaled to high-resolution spherical data for SISR quality measurement. We extensively evaluate two state-of-the-art SISR methods using widely used full-reference SISR quality metrics adapted to our designed framework. In addition, our study reveals that most objective metric show high performance over CNN based SISR, while subjective tests favors GAN-based architectures.

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Lamichhane, Kamal, Marco Carli, and Federica Battisti. "Saliency-based deep blind image quality assessment." Electronic Imaging 2021, no. 9 (January 18, 2021): 225–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.9.iqsp-225.

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Assessing the quality of images is a challenging task. To achieve this goal, the images must be evaluated by a pool of subjects following a well-defined assessment protocol or an objective quality metric must be defined. In this contribution, an objective metric based on neural networks is proposed. The model takes into account the human vision system by computing a saliency map of the image under test. The system is based on two modules: the first one is trained using normalized distorted images. It learns the features from the original and the distorted images and the estimated saliency map. Furthermore, an estimate of the prediction error is performed. The second module (non-linear regression module) is trained with the available subjective scores. The performances of the proposed metric have been evaluated by using state of the art quality assessment datasets. The achieved results show the effectiveness of the proposed system in matching the subjective quality score.

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Khuri, Shukri F. "Safety, Quality, and the National Surgical Quality Improvement Program." American Surgeon 72, no. 11 (November 2006): 994–98. http://dx.doi.org/10.1177/000313480607201103.

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The Institute of Medicine 1999 publication, To Err is Human, focused attention on preventable provider errors in surgery, and prompted numerous new national initiatives to improve patient safety. It is uncertain whether these initiatives have actually improved patient safety, mainly because of the lack of a quantitative metric for the assessment of patient safety in surgery. A 15-year experience with the National Surgical Quality Improvement Program, which originated in the Veteran's Administration in 1991 and was recently made available to the private sector, prompts the surgical community to place patient safety in surgery within a much larger conceptual framework than that of the Institute of Medicine report, and provides a quantitative metric for the assessment of patient safety initiatives. This conceptual framework defines patient safety in surgery as safety from all adverse outcomes (not only preventable errors and sentinel events); regards safety as an integral part of quality of surgical care; recognizes that adverse outcomes, and hence patient safety, are primarily determined by quality of systems of care; and uses comparative risk-adjusted outcome data as a metric for the identification of system problems and for the assessment and improvement of patient safety from adverse outcomes.

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Heinrich, Bernd, and Mathias Klier. "Metric-based data quality assessment — Developing and evaluating a probability-based currency metric." Decision Support Systems 72 (April 2015): 82–96. http://dx.doi.org/10.1016/j.dss.2015.02.009.

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Larabi, Mohamed-Chaker, Audrey Girard, Sami Jaballah, and Fan Yu. "Benchmark of 2D quality metrics for the assessment of 360-deg images." Color and Imaging Conference 2019, no. 1 (October 21, 2019): 262–67. http://dx.doi.org/10.2352/issn.2169-2629.2019.27.47.

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Omnidirectional or 360-degree images are becoming very popular in many applications and several challenges are raised because of both the nature and the representation of the data. Quality assessment is one of them from two different points of view: objectively or subjectively. In this paper, we propose to study the performance of different metrics belonging to various categories including simple mathematical metrics, humand perception based metrics and spherically optimized metrics. The performance of these metrics is measured using different tools such as PLCC, SROCC, KROCC and RMSE based on the only publically available database from Nanjing university. The results show that the metric that are considered as optimized for 360 degrees images are not providing the best correlation with the human judgement of the quality.

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Torkhani, Fakhri, Jean-Marc Chassery, and Kai Wang. "A Curvature-Tensor-Based Perceptual Quality Metric for 3D Triangular Meshes." Machine Graphics and Vision 23, no. 1/2 (January 14, 2012): 59–82. http://dx.doi.org/10.22630/mgv.2014.23.1.4.

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Perceptual quality assessment of 3D triangular meshes is crucial for a variety of applications. In this paper, we present a new objective metric for assessing the visual difference between a reference triangular mesh and its distorted version produced by lossy operations, such as noise addition, simplification, compression and watermarking. The proposed metric is based on the measurement of the distance between curvature tensors of the two meshes under comparison. Our algorithm uses not only tensor eigenvalues (i.e., curvature amplitudes) but also tensor eigenvectors (i.e., principal curvature directions) to derive a perceptually-oriented tensor distance. The proposed metric also accounts for the visual masking effect of the human visual system, through a roughness-based weighting of the local tensor distance. A final score that reflects the visual difference between two meshes is obtained via a Minkowski pooling of the weighted local tensor distances over the mesh surface. We validate the performance of our algorithm on four subjectively-rated visual mesh quality databases, and compare the proposed method with state-of-the-art objective metrics. Experimental results show that our approach achieves high correlation between objective scores and subjective assessments.

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Elloumi, Nessrine, Habiba Loukil Hadj Kacem, Nilanjan Dey, Amira S. Ashour, and Med Salim Bouhlel. "Perceptual Metrics Quality." International Journal of Service Science, Management, Engineering, and Technology 8, no. 1 (January 2017): 63–80. http://dx.doi.org/10.4018/ijssmet.2017010105.

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A 3D mesh can be subjected to different types of operations, such as compression, watermarking etc. Such processes lead to geometric distortions compared to the original version. In this context, quantifying the resultant modifications to the original mesh and evaluating the perceptual quality of degraded meshes become a critical issue. The perceptual 3D meshes quality is central in several applications to preserve the visual appearance of these treatments. The used metrics results have to be well correlated to the visual perception of humans. Although there are objective metrics, they do not allow the prediction of the perceptual quality, and do not include the human visual system properties. In the current work, a comparative study between the perceptual quality assessment metrics for 3D meshes was conducted. The experimental study on subjective database published by LIRIS / EPFL was used to test and to validate the results of six metrics. The results established that the Mesh Structural Distortion Measure metric achieved superior results compared to the other metrics.

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Sandić-Stanković, Dragana, Dragan Kukolj, and Patrick Le Callet. "Multi–Scale Synthesized View Assessment Based on Morphological Pyramids." Journal of Electrical Engineering 67, no. 1 (January 1, 2016): 3–11. http://dx.doi.org/10.1515/jee-2016-0001.

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Abstract The Depth-Image-Based-Rendering (DIBR) algorithms used for 3D video applications introduce geometric distortions affecting the edge coherency in the synthesized images. In order to better deal with specific geometric distortions in the DIBR synthesized images, we propose full-reference metric based on multi-scale pyramid decompositions using morphological filters. The non-linear morphological filters used in multi-scale image decompositions maintain important geometric information such as edges across different resolution levels. We show that PSNR has particularly good agreement with human judgment when it is calculated between detailed images at higher scales of morphological pyramids. Consequently, we propose reduced morphological pyramid peak signal-to-noise ratio metric (MP-PSNR), taking into account only mean squared errors between pyramids’ images at higher scales. Proposed computationally efficient metric achieves significantly higher correlation with human judgment compared to the state-of-the-art image quality assessment metrics and compared to the tested metric dedicated to synthesis-related artifacts.

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DENG, CHENG, JIE LI, YIFAN ZHANG, DONGYU HUANG, and LINGLING AN. "AN IMAGE QUALITY METRIC BASED ON BIOLOGICALLY INSPIRED FEATURE MODEL." International Journal of Image and Graphics 11, no. 02 (April 2011): 265–79. http://dx.doi.org/10.1142/s0219467811004093.

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Objective image quality assessment (IQA) metrics have been widely applied to imaging systems to preserve and enhance the perceptual quality of images being processed and transmitted. In this paper, we present a novel IQA metric based on biologically inspired feature model (BIFM) and structural similarity index (SSIM). The SSIM index map is first generated through the well-known IQA metric SSIM between the reference image and the distorted image. Then, saliency map of the distorted image is extracted via BIF to define the most salient image locations. Finally, according to the saliency map, a feature weighting model is employed to define the different weights for the different samples in the SSIM index map. Experimental results confirm that the proposed IQA metric improves the performance over PSNR and SSIM under various distortion types in terms of different evaluation criteria.

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Tian, Shishun, Lu Zhang, Luce Morin, and Olivier Deforges. "NIQSV+: A No-Reference Synthesized View Quality Assessment Metric." IEEE Transactions on Image Processing 27, no. 4 (April 2018): 1652–64. http://dx.doi.org/10.1109/tip.2017.2781420.

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Jin, Xin, Mei Yu, Shanshan Liu, Yang Song, and Gangyi Jiang. "New image quality assessment metric based on distortion classification." International Journal of Information and Communication Technology 11, no. 2 (2017): 243. http://dx.doi.org/10.1504/ijict.2017.086251.

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Jiang, Gangyi, Yang Song, Mei Yu, Shanshan Liu, and Xin Jin. "New image quality assessment metric based on distortion classification." International Journal of Information and Communication Technology 11, no. 2 (2017): 243. http://dx.doi.org/10.1504/ijict.2017.10007026.

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Lavoué, Guillaume. "A Multiscale Metric for 3D Mesh Visual Quality Assessment." Computer Graphics Forum 30, no. 5 (August 2011): 1427–37. http://dx.doi.org/10.1111/j.1467-8659.2011.02017.x.

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Yu, Qian, Wei Dong, and Chang N. Zhang. "RCBM: a rough content-based image quality assessment metric." International Journal of Granular Computing, Rough Sets and Intelligent Systems 3, no. 1 (2013): 44. http://dx.doi.org/10.1504/ijgcrsis.2013.054126.

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LU, WEN, LIHUO HE, WENJIAN TANG, FEI GAO, and WEILONG HOU. "A NOVEL COMPRESSED IMAGES QUALITY METRIC." International Journal of Image and Graphics 11, no. 02 (April 2011): 281–92. http://dx.doi.org/10.1142/s021946781100410x.

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As the performance indicator of the image processing algorithms or systems, image quality assessment (IQA) has attracted the attention of many researchers. Aiming to the widely used compression standards, JPEG and JPEG2000, we propose a new no reference (NR) metric for compressed images to do IQA. This metric exploits the causes of distortion by JPEG and JPEG2000, employs the directional discrete cosine transform (DDCT) to obtain the detail and directional information of the images and incorporates with the visual perception to obtain the image quality index. Experimental results show that the proposed metric not only has outstanding performance on JPEG and JPEG2000 images, but also applicable to other types of artifacts.

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Грицюк, Ю. І., and Т. О. Муха. "Methods of determination of quality of software." Scientific Bulletin of UNFU 30, no. 1 (February 27, 2020): 158–67. http://dx.doi.org/10.36930/40300127.

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Developed modern software tool for determining the quality of software (SW) techniques metric analysis. The software allows you to use quality metrics to calculate the corresponding metric and determine the value of the complex index of quality software product. Clarified the quality assessment process, software analyzes the concept of the quality of the software product as an object of standardization and quality levels of performance models of the software. This allowed the opportunity to improve the quality of software by generating the relevant requirements of the criteria for quality evaluation. It is also possible to make the improvement of the metric analysis of models of its quality and its quantitative measurement methods in all phases of a software project. It was revealed that the driving force behind the success of software projects is the desire of their leaders to develop such software, which would have a certain value. It should be important for certain tasks or to achieve tactical and strategic objectives. The value of the software can be expressed in the form of its value, or in some other form. The customer usually has their own idea of the maximum cost of investing in the development of software. These funds profit it expects to achieve in the case of the main goals of using the software. It can also have a vision of the functionality of software and certain expectations of its quality. The features of the use of the metric analysis for determining the quality of the software, revealed the lack of uniform standards for the metric. Therefore, each supplier of its measurement system offers its own methods of evaluating the quality of software and associated metrics. Also it is challenging the interpretation of metric values, since for the majority of users of its software metrics and their values are not absolutely clear and informative. It was found that the main parameters of the choice of an embodiment of the software is its cost, the duration of the development process and the reputation of the designer of the company. But the decisions taken on the basis of these parameters, not always guarantee proper quality of the software.

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Wang, Hui, Xiaojuan Hu, Hui Xu, Shiyin Li, and Zhaolin Lu. "No-Reference Quality Assessment Method for Blurriness of SEM Micrographs with Multiple Texture." Scanning 2019 (June 2, 2019): 1–15. http://dx.doi.org/10.1155/2019/4271761.

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Scanning electron microscopy (SEM) plays an important role in the intuitive understanding of microstructures because it can provide ultrahigh magnification. Tens or hundreds of images are regularly generated and saved during a typical microscopy imaging process. Given the subjectivity of a microscopist’s focusing operation, blurriness is an important distortion that debases the quality of micrographs. The selection of high-quality micrographs using subjective methods is expensive and time-consuming. This study proposes a new no-reference quality assessment method for evaluating the blurriness of SEM micrographs. The human visual system is more sensitive to the distortions of cartoon components than to those of redundant textured components according to the Gestalt perception psychology and the entropy masking property. Micrographs are initially decomposed into cartoon and textured components. Then, the spectral and spatial sharpness maps of the cartoon components are extracted. One metric is calculated by combining the spatial and spectral sharpness maps of the cartoon components. The other metric is calculated on the basis of the edge of the maximum local variation map of the cartoon components. Finally, the two metrics are combined as the final metric. The objective scores generated using this method exhibit high correlation and consistency with the subjective scores.

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Еремеев, Олег Игоревич, Владимир Васильевич Лукин, and Krzysztof Okarma. "КОМБІНОВАНА МЕТРИКА ВІЗУАЛЬНОЇ ЯКОСТІ ЗОБРАЖЕНЬ ДИСТАНЦІЙНОГО ЗОНДУВАННЯ НА ОСНОВІ НЕЙРОННОЇ МЕРЕЖІ." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 4 (November 27, 2020): 4–15. http://dx.doi.org/10.32620/reks.2020.4.01.

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The wide distribution of images of remote sensing (RS) of the Earth in various application areas makes it important to ensure the high quality of such images, which is important to identify necessary information. The complexity of the systems and the impact of various physical processes cause a significant number of distortions that lead to image corruption and possible loss of information. The use of processing methods that should reduce the impact of such factors requires control of their work, which uses quantitative indicators of visual quality. The article considers the task of creating a combined visual quality metric based on an artificial neural network (ANN), which provides high accuracy of visual quality assessment and stability of work on the noise characteristic of the RS. The problem of analysis of RS distortions is considered and the approach of using the database of test images TID2013 for verification on typical RS distortions is offered. The analysis of well-known visual quality metrics and their suitability for the estimation of such images is carried out. According to its results, it was determined that the best metrics provide the accuracy of image quality assessment for RS tasks at the level of 0.93 according to Spearman's rank-order correlation coefficient with subjective estimates of the TID2013 image database. The joint application of existing quality metrics allows eliminating the shortcomings of each of them and increasing the overall efficiency, so the article considers the problems and defines the requirements for creating a combined metric involving a neural network. A method of limiting the number of involved quality metrics with the involvement of Lasso regularization is proposed, which allows determining the most informative features (quality metrics) and simplifying the procedure of selection and reduction of their number. A study was conducted on the influence of the metric selection criterion and quantity on the accuracy of the combined metric. The influence of the structure of the neural network, the number of hidden layers, and the number of neurons in them are also analyzed. Based on the obtained results, the best implementation of ANN was selected, which with the involvement of 16 visual quality metrics allows achieving the accuracy of visual quality assessment at 0.97 according to Spearman's correlation with subjective estimates of the TID2013 database.

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Tashtoush, Yahya M., Aisha Zaidan, and Izzat M. Alsmadi. "Implications for Website Trust and Credibility Assessment." International Journal of E-Entrepreneurship and Innovation 3, no. 4 (October 2012): 17–33. http://dx.doi.org/10.4018/jeei.2012100102.

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With the expansion of the Internet services provided to users to cover almost all areas that were dominated by traditional face-to-face and location based businesses, one of the major challenges for such expansion is security and its related concerns. Customers or users need to trust the websites they visit in terms of the information or content. This research proposes a new formula for evaluating the credibility (called XD TRank) metric of websites. A case study of 40 selected websites in Jordan is used to assess the proposed credibibility metric. The metrics required to assess Websites and pages credibility are collected and evaluated based on 25 existing metrics and built a model using SPSS by applying stepwise linear regression analysis to predict the XD TRank. Results showed that there is a broad range of metrics that affect the credibility of a website or a webpage and their impact on credibility may vary on their significancy or impact on the trust rank metric. For e-business in particular, trust rank metrics can be used part of quality assurance and auditing processes. Those can be important assets for users to be able to distinguish known, popular and reliable e-commerce websites from spammers or websites which try to trick novice users. Trust rank can be also used like a logo in all Website pages to alert users if they were redirected to phishing pages.

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M. Taaffe, Kevin, Robert William Allen, and Lindsey Grigg. "Performance metrics analysis for aircraft maintenance process control." Journal of Quality in Maintenance Engineering 20, no. 2 (May 6, 2014): 122–34. http://dx.doi.org/10.1108/jqme-07-2012-0022.

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Purpose – Performance measurements or metrics are that which measure a company's performance and behavior, and are used to help an organization achieve and maintain success. Without the use of performance metrics, it is difficult to know whether or not the firm is meeting requirements or making desired improvements. During the course of this study with Lockheed Martin, the research team was tasked with determining the effectiveness of the site's existing performance metrics that are used to help an organization achieve and maintain success. Without the use of performance metrics, it is difficult to know whether or not the firm is meeting requirements or making desired improvements. The paper aims to discuss these issues. Design/methodology/approach – Research indicates that there are five key elements that influence the success of a performance metric. A standardized method of determining whether or not a metric has the right mix of these elements was created in the form of a metrics scorecard. Findings – The scorecard survey was successful in revealing good metric use, as well as problematic metrics. In the quality department, the Document Rejects metric has been reworked and is no longer within the executive's metric deck. It was also recommended to add root cause analysis, and to quantify and track the cost of non-conformance and the overall cost of quality. In total, the number of site wide metrics has decreased from 75 to 50 metrics. The 50 remaining metrics are undergoing a continuous improvement process in conjunction with the use of the metric scorecard tool developed in this research. Research limitations/implications – The metrics scorecard should be used site-wide for an assessment of all metrics. The focus of this paper is on the metrics within the quality department. Practical implications – Putting a quick and efficient metrics assessment technique in place was critical. With the leadership and participation of Lockheed Martin, this goal was accomplished. Originality/value – This paper presents the process of metrics evaluation and the issues that were encountered during the process, including insights that would not have been easily documented without this mechanism. Lockheed Martin Company has used results from this research. Other industries could also apply the methods proposed here.

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Greeshma, M. S., and V. R. Bindu. "Super-resolution Quality Criterion (SRQC): a super-resolution image quality assessment metric." Multimedia Tools and Applications 79, no. 47-48 (August 1, 2020): 35125–46. http://dx.doi.org/10.1007/s11042-020-09352-0.

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Che, Li, and Fengju Kang. "Exploring the efficiency of image metric for assessing the visual quality of 3D mesh model." International Journal of Modeling, Simulation, and Scientific Computing 09, no. 06 (December 2018): 1850056. http://dx.doi.org/10.1142/s1793962318500563.

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Recent developments in 3D graphics technology have led to extensive processes on 3D meshes (e.g., compression, simplification, transmission and watermarking), these processes unavoidably cause the visual perceptual degradation of the 3D objects. The existing mesh visual quality evaluation metrics either require topology constrain or fail to reflect the perceived visual quality. Meanwhile, for the 3D objects that are observed on 2D screens by the users, it is reasonable to apply image metric to assess the distortion caused by mesh simplification. We attempt to explore the efficiency of image metric for assessing the visual fidelity of the simplified 3D model in this paper. For this purpose, several latest and most effective image metrics, 2D snapshots, number and pooling algorithms are involved in our study, and finally tested on the IEETA simplification database. The statistical data allow the researcher to select the optimal parameter for this image-based mesh visual quality assessment and provide a new perspective for the design and performance assessment of mesh simplification algorithms.

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Chandrakanth, T., and B. Sandhya. "Analysis of SSIM based Quality Assessment across Color Channels of Images." International Journal of System Dynamics Applications 4, no. 3 (July 2015): 30–42. http://dx.doi.org/10.4018/ijsda.2015070102.

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Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

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Ni, Jun, Zi Yin Li, and Hua Cai Chen. "No-Reference Image Quality Assessment Based on Visual Perception." Advanced Engineering Forum 1 (September 2011): 325–29. http://dx.doi.org/10.4028/www.scientific.net/aef.1.325.

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No-reference image quality assessment is an important issue for video compression and communication. This work presents a no-reference objective image/video sharpness method based on visual perception metric (VPM). The algorithm gets image typical edge and edge width firstly, and then gets gray contrast of typical edge region, finally utilizes these factors to integrate a probability summation assessment model. The proposed metric is able to predict the amount of sharpness in image with different content. Experimental results show that this method is consistent with subjective assessment of human being and can be use to describe the visual perception of image effectively.

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Wang, X., and A. Subic. "Psychoacoustic modelling of vehicle side mirror power-fold actuator noise characteristics." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 225, no. 6 (April 13, 2011): 1419–29. http://dx.doi.org/10.1177/0954406211399514.

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A study of vehicle side mirror power-fold actuator noise characteristic was undertaken, which seeks to correlate subjective evaluation with objective measurements as a basis for development of a product sound quality control algorithm. Psychoacoustic metrics were extracted from the product sound measurements and analysed for manufacturing quality assessment. Two approaches were explored in this study; one is a multiple metric sequential pass-through gate approach and the other is the least square fit regression approach, where measured relevant psychoacoustic metrics are modelled against subjective rating data provided by product sound quality evaluation experts. The ‘gate’ approach using sound pressure level, roughness, and tonality was successfully implemented to segregate bad power-fold actuators from good ones in terms of sound quality. A non-linear, two metric regression algorithm assessing what is a ‘good’ or a ‘bad’ actuator, was then developed and validated through comparison with a linear eight metric regression algorithm. Based on correlation of objective measurement and subjective evaluation results for given product samples, the diagnostic methodology developed in this research is applicable to other products for noise diagnostics and quality control.

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Tian, Jieni, Jiangping Yuan, Hua Li, Danyang Yao, and Guangxue Chen. "Advanced Surface Color Quality Assessment in Paper-Based Full-Color 3D Printing." Materials 14, no. 4 (February 4, 2021): 736. http://dx.doi.org/10.3390/ma14040736.

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Color 3D printing allows for 3D-printed parts to represent 3D objects more realistically, but its surface color quality evaluation lacks comprehensive objective verification considering printing materials. In this study, a unique test model was designed and printed using eco-friendly and vivid paper-based full-color 3D printing as an example. By measuring the chromaticity, roughness, glossiness, and whiteness properties of 3D-printed surfaces and by acquiring images of their main viewing surfaces, this work skillfully explores the correlation between the color representation of a paper-based 3D-printed coloring layer and its attached underneath blank layer. Quantitative analysis was performed using ΔE*ab, feature similarity index measure of color image (FSIMc), and improved color-image-difference (iCID) values. The experimental results show that a color difference on color-printed surfaces exhibits a high linear correlation trend with its FSIMc metric and iCID metric. The qualitative analysis of microscopic imaging and the quantitative analysis of the above three surface properties corroborate the prediction of the linear correlation between color difference and image-based metrics. This study can provide inspiration for the development of computational coloring materials for additive manufacturing.

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Mishra,, Anjay Kumar. "Assessment of Household Cement Consumption Pattern in Pokhara Metropolitan City." Journal of Advanced Research in Construction and Urban Architecture 6, no. 1 (April 12, 2021): 12–20. http://dx.doi.org/10.24321/2456.9925.202102.

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Cement is a major construction material used in civil engineering works due to which its demand is very high. A proper cement brand selection is a tough task. Different brands have different pricing and quality because they are from different origin and industries. The consumers and suppliers of the cement market may feel that every brand they are buying and selling is of good quality. Most of the cement may conform to the minimum standard for use. The study has been focused to assess the consumption of different cement brands available in the Pokhara metropolitan city. To carry out the research, cement supplier’s data and field data were collected. Consumers within the study area were considered during the survey. Visual inspection of maximum sites was done. The different brands of cement in use at the site were examined by field survey and analysis was done on SPSS software to obtain the results. Maximum cement consumers choose Shivam (30%) in OPC type and Brij cement (25%) in PPC type. During the selection of the cement, consumers are mainly affected by contractors with (35%) without any quality test of cement. 15% of the cement consumers don’t know about the brand of cement they are using in their household construction. 77.50% of the consumers don’t do quality assurance with engineers during household construction. 70% of the cement consumers are unknown about the concrete ratio in structural members. 97.5% of the cement consumers are unaware of the manufacturing date. Only 12.50% of the cement consumers are affected by advertisement of cement. 80% of the RMC company uses Shivam cement and 20% uses Argakhachi cement. A positive increasing trend of annual cement consumption is seen from 2070 BS to 2076 BS. Cement consumption forecasting for 2080 BS would be 289942.089 metric ton with upper bound and lower bound consumption being 209742.725 metric ton and 370141.450 metric ton respectively. Cement consumption from RMC suppliers in the study area in 2080 BS would be 49125.005 metric ton with upper bound and lower bound consumption being 59572.830 metric ton and 38677.190 metric ton respectively.

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Okarma, Krzysztof, Wojciech Chlewicki, Mateusz Kopytek, Beata Marciniak, and Vladimir Lukin. "Entropy-Based Combined Metric for Automatic Objective Quality Assessment of Stitched Panoramic Images." Entropy 23, no. 11 (November 17, 2021): 1525. http://dx.doi.org/10.3390/e23111525.

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Quality assessment of stitched images is an important element of many virtual reality and remote sensing applications where the panoramic images may be used as a background as well as for navigation purposes. The quality of stitched images may be decreased by several factors, including geometric distortions, ghosting, blurring, and color distortions. Nevertheless, the specificity of such distortions is different than those typical for general-purpose image quality assessment. Therefore, the necessity of the development of new objective image quality metrics for such type of emerging applications becomes obvious. The method proposed in the paper is based on the combination of features used in some recently proposed metrics with the results of the local and global image entropy analysis. The results obtained applying the proposed combined metric have been verified using the ISIQA database, containing 264 stitched images of 26 scenes together with the respective subjective Mean Opinion Scores, leading to a significant increase of its correlation with subjective evaluation results.

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Ferenc, Rudolf, Zoltán Tóth, Gergely Ladányi, István Siket, and Tibor Gyimóthy. "A public unified bug dataset for java and its assessment regarding metrics and bug prediction." Software Quality Journal 28, no. 4 (June 3, 2020): 1447–506. http://dx.doi.org/10.1007/s11219-020-09515-0.

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AbstractBug datasets have been created and used by many researchers to build and validate novel bug prediction models. In this work, our aim is to collect existing public source code metric-based bug datasets and unify their contents. Furthermore, we wish to assess the plethora of collected metrics and the capabilities of the unified bug dataset in bug prediction. We considered 5 public datasets and we downloaded the corresponding source code for each system in the datasets and performed source code analysis to obtain a common set of source code metrics. This way, we produced a unified bug dataset at class and file level as well. We investigated the diversion of metric definitions and values of the different bug datasets. Finally, we used a decision tree algorithm to show the capabilities of the dataset in bug prediction. We found that there are statistically significant differences in the values of the original and the newly calculated metrics; furthermore, notations and definitions can severely differ. We compared the bug prediction capabilities of the original and the extended metric suites (within-project learning). Afterwards, we merged all classes (and files) into one large dataset which consists of 47,618 elements (43,744 for files) and we evaluated the bug prediction model build on this large dataset as well. Finally, we also investigated cross-project capabilities of the bug prediction models and datasets. We made the unified dataset publicly available for everyone. By using a public unified dataset as an input for different bug prediction related investigations, researchers can make their studies reproducible, thus able to be validated and verified.

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Zhang, Haopeng, Bo Yuan, Bo Dong, and Zhiguo Jiang. "No-Reference Blurred Image Quality Assessment by Structural Similarity Index." Applied Sciences 8, no. 10 (October 22, 2018): 2003. http://dx.doi.org/10.3390/app8102003.

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No-reference (NR) image quality assessment (IQA) objectively measures the image quality consistently with subjective evaluations by using only the distorted image. In this paper, we focus on the problem of NR IQA for blurred images and propose a new no-reference structural similarity (NSSIM) metric based on re-blur theory and structural similarity index (SSIM). We extract blurriness features and define image blurriness by grayscale distribution. NSSIM scores an image quality by calculating image luminance, contrast, structure and blurriness. The proposed NSSIM metric can evaluate image quality immediately without prior training or learning. Experimental results on four popular datasets show that the proposed metric outperforms SSIM and well-matched to state-of-the-art NR IQA models. Furthermore, we apply NSSIM with known IQA approaches to blurred image restoration and demonstrate that NSSIM is statistically superior to peak signal-to-noise ratio (PSNR), SSIM and consistent with the state-of-the-art NR IQA models.

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Condorelli, F., and F. Rinaudo. "BENCHMARK OF METRIC QUALITY ASSESSMENT IN PHOTOGRAMMETRIC RECONSTRUCTION FOR HISTORICAL FILM FOOTAGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W11 (May 4, 2019): 443–48. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w11-443-2019.

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<p><strong>Abstract.</strong> Quality assessment in photogrammetric processing is fundamental to obtain metric information and to reconstruct 3D models of Cultural Heritage, especially when it has been lost or changed over time. The determination of metric precision is technically challenging when dealing with historical films and videos that in many cases represent the only remaining traces of this heritage, which is useful for architectural, archaeological and restoration studies. This paper examines the suitability of existing photogrammetric software to evaluate the maximum possible metric accuracy for processing videos shot with fixed camera motions. In order to evaluate the metric quality obtained processing historical film footage with photogrammetric techniques, a benchmark was created on a new video dataset with the aim of reproducing the camera motions in which old video were shot. Three different camera motions were considered: Up/Down Motion-Tilting, Left/Right Motion-Trucking and Rolling Motion-Panning. The methodology was experimented on Valentino Castle in Turin, a monument inscribed in the UNESCO World Heritage List. Data were processed with the implementation of open source Structure-from-Motion algorithms and the results were analysed for the evaluation of metric quality. Results show the different maximum precision assessments according to the different typologies of camera motion. This research provides fundamental support to historical studies on Cultural Heritage, creating a sharing standard with zero-cost data and tools useful for both geomatics and restorers.</p>

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Okarma, Krzysztof, and Mateusz Kopytek. "Improved Combined Metric for Automatic Quality Assessment of Stitched Images." Applied Sciences 12, no. 20 (October 12, 2022): 10284. http://dx.doi.org/10.3390/app122010284.

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An automatic quality assessment of stitched images is an essential task in image analysis and is particularly useful not only in the creation of general-purpose panoramic images but also in terrain exploration and mapping made by mobile robots and drones. In Visual Simultaneous Localization and Mapping (VSLAM) solutions, the environment maps acquired by cameras mounted on the mobile robots may be captured in dynamically changing lighting conditions and subject to some other distortions influencing the final quality of the panoramic images representing the robot’s surroundings. Such images may also be used for motion planning and visual navigation for other robots, e.g., in follow-the-leader scenarios. Another relevant application area of panoramic imaging is Virtual Reality (VR), particularly head-mounted displays, where perceived image quality is even more important. Hence, automatic quality evaluations of stitched images should be made using algorithms that are both sensitive to various types of distortions and strongly consistent with subjective quality impression. The approach presented in this paper extends the state-of-the-art metric known as the Stitched Image Quality Evaluator (SIQE) by embedding it with with some additional features using the proposed new combination scheme. The developed combined metric based on a nonlinear combination of the SIQE and additional features led to a substantially higher correlation with the subjective quality scores.

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Rajagopal, Heshalini, Norrima Mokhtar, Anis Salwa Mohd Khairuddin, Wan Khairunizam, Zuwairie Ibrahim, Asrul Bin Adam, and Wan Amirul Bin Wan Mohd Mahiyidin. "A No-Reference Image Quality Assessment Metric for Wood Images." Journal of Robotics, Networking and Artificial Life 8, no. 2 (2021): 127. http://dx.doi.org/10.2991/jrnal.k.210713.012.

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Kaur, Roopdeep, Gour Karmakar, and Feng Xia. "A Reliable Image Quality Assessment Metric: Evaluation Using Camera Impacts." Pattern Recognition and Image Analysis 32, no. 3 (September 2022): 551–60. http://dx.doi.org/10.1134/s105466182203018x.

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Journal articles on the topic 'Metric quality assessment'

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