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Статті в журналах з теми "Subjective and Objective Image Quality Assessment"
Park, Hyung-ju, and Dong-hwan Har. "Subjective image quality assessment based on objective image quality measurement factors." IEEE Transactions on Consumer Electronics 57, no. 3 (August 2011): 1176–84. http://dx.doi.org/10.1109/tce.2011.6018872.
Повний текст джерелаAfnan, Afnan, Faiz Ullah, Yaseen Yaseen, Jinhee Lee, Sonain Jamil, and Oh-Jin Kwon. "Subjective Assessment of Objective Image Quality Metrics Range Guaranteeing Visually Lossless Compression." Sensors 23, no. 3 (January 23, 2023): 1297. http://dx.doi.org/10.3390/s23031297.
Повний текст джерелаZhang, Huiqing, Donghao Li, Yibing Yu, and Nan Guo. "Subjective and Objective Quality Assessments of Display Products." Entropy 23, no. 7 (June 26, 2021): 814. http://dx.doi.org/10.3390/e23070814.
Повний текст джерелаZhang, Chun E., Fan Ci Guo, and Ke Xiong. "Towards Subjective Consistency: An Effective Objective Quality Assessment Algorithm for Binary Image." Key Engineering Materials 474-476 (April 2011): 143–50. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.143.
Повний текст джерелаZelmati, Omar, Boban Bondžulić, Boban Pavlović, Ivan Tot, and Saad Merrouche. "Study of subjective and objective quality assessment of infrared compressed images." Journal of Electrical Engineering 73, no. 2 (April 1, 2022): 73–87. http://dx.doi.org/10.2478/jee-2022-0011.
Повний текст джерелаPark, Hyung-Ju, and Dong-Hwan Har. "Correlation Research between Objective and Subjective Image Quality Assessment." Journal of the Korea Contents Association 11, no. 8 (August 28, 2011): 68–76. http://dx.doi.org/10.5392/jkca.2011.11.8.068.
Повний текст джерелаShrestha, Prarthana, Rik Kneepkens, Gijs van Elswijk, Jeroen Vrijnsen, Roxana Ion, Dirk Verhagen, Esther Abels, Dirk Vossen, and and Bas Hulsken. "Objective and Subjective Assessment of Digital Pathology Image Quality." AIMS Medical Science 2, no. 1 (2015): 65–78. http://dx.doi.org/10.3934/medsci.2015.1.65.
Повний текст джерелаGood, Walter F., David Gur, John H. Feist, F. Leland Thaete, Carl R. Fuhrman, Cynthia A. Britton, and B. Simon Slasky. "Subjective and objective assessment of image quality—A comparison." Journal of Digital Imaging 7, no. 2 (May 1994): 77–78. http://dx.doi.org/10.1007/bf03168426.
Повний текст джерелаOszust, Mariusz. "No-Reference Image Quality Assessment with Local Gradient Orientations." Symmetry 11, no. 1 (January 16, 2019): 95. http://dx.doi.org/10.3390/sym11010095.
Повний текст джерелаYang, Yang, Jun Ming, and Nenghai Yu. "Color Image Quality Assessment Based on CIEDE2000." Advances in Multimedia 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/273723.
Повний текст джерелаДисертації з теми "Subjective and Objective Image Quality Assessment"
Sendjasni, Abderrezzaq. "Objective and subjective quality assessment of 360-degree images." Electronic Thesis or Diss., Poitiers, 2023. http://www.theses.fr/2023POIT2251.
Повний текст джерела360-degree images, a.k.a. omnidirectional images, are in the center of immersive media. With the increase in demands of the latter, mainly thanks to the offered interactive and immersive experience, it is paramount to provide good quality of experience (QoE). This QoE is significantly impacted by the quality of the content. Like any type of visual signal, 360-degree images go through a sequence of processes including encoding, transmission, decoding, and rendering. Each of these processes has the potential to introduce distortions to the content. To improve the QoE, image quality assessment (IQA) is one of the strategies to be followed. This thesis addresses the quality evaluation of 360-degree images from the objective and subjective perspectives. By focusing on the influence of Head Mounted Displays (HMDs) on the perceived quality of 360-degree images, a psycho-visual study is designed and carried out using four different devices. For this purpose, a 360-degree image datasets is created and a panel of observers is involved. The impact of HMDs on the quality ratings is identified and highlighted as an important factor to consider when con- ducting subjective experiments for 360-degree images. From the objective perspective, we first comprehensively benchmarked several convolutional neural network (CNN) models under various configurations. Then, the processing chain of CNN-based 360-IQA is improved at different scales, from input sampling and representation to aggregating quality scores. Based on the observations of the above studies as well as the benchmark, two 360-IQA models based on CNNs are proposed to accurately predict the quality of 360-degree images. The obtained observations and conclusions from the various contributions shall bring insights for assessing the quality of 360-degree images
360-graders bilder, også kjent som rundstrålende bilder, er i sentrum av oppslukende medier. Med økningen i forventninger til sistnevnte, hovedsakelig takket være den aktiverte interaktive og oppslukende opplevelse, er det avgjørende å gi god kvaliteten på opplevelsen (QoE).Denne QoE er betydelig påvirket av kvaliteten på innholdet. Som alle typer visuelle signaler går 360-graders bilder gjennom en sekvens av prosesser, inkludert koding, overføring, dekoding og gjengivelse. Hver av disse prosessene har potensial til å introdusere forvrengninger til innholdet.For å forbedre QoE er vurdering av bildekvalitet (IQA) en av strategiene å følge. Denne oppgaven tar for seg kvalitetsevaluering av 360-graders bilder fra objektive og subjektive perspektiver. Ved å fokusere på påvirkningen av Head Mounted Displays (HMD-er) på den oppfattede kvaliteten til 360-graders bilder, er en psyko-visuell studie designet og utført ved hjelp av fire forskjellige enheter. For dette formålet opprettes et 360-graders bildedatasett og et panel av observatører er involvert. Virkningen av HMD-er på valitetsvurderingene identifiseres og fremheves som en viktig faktor når du utfører subjektive eksperimenter for 360-graders bilder.Fra det objektive perspektivet benchmarket vi først flere konvolusjonelle nevrale nettverk (CNN) under forskjellige konfigurasjoner. Deretter forbedres prosesseringskjeden til CNN-baserte 360-IQA i forskjellige skalaer, fra input-sampling og representasjon til aggregering av kvalitetspoeng. Basert på observasjonene av de ovenfornevnte studiene så vel som benchmark, foreslås to 360-IQA-modeller basert på CNN-er for å nøyaktig forutsi kvaliteten på 360-graders bilder.De innhentede observasjonene og konklusjonene fra de ulike bidragene skal gi innsikt for å vurdere kvaliteten på 360-graders bilder
Zerman, Emin. "Evaluation et analyse de la qualité vidéo à haute gamme dynamique." Electronic Thesis or Diss., Paris, ENST, 2018. http://www.theses.fr/2018ENST0003.
Повний текст джерелаIn the last decade, high dynamic range (HDR) image and video technology gained a lot of attention, especially within the multimedia community. Recent technological advancements made the acquisition, compression, and reproduction of HDR content easier, and that led to the commercialization of HDR displays and popularization of HDR content. In this context, measuring the quality of HDR content plays a fundamental role in improving the content distribution chain as well as individual parts of it, such as compression and display. However, HDR visual quality assessment presents new challenges with respect to the standard dynamic range (SDR) case. The first challenge is the new conditions introduced by the reproduction of HDR content, e.g. the increase in brightness and contrast. Even though accurate reproduction is not necessary for most of the practical cases, accurate estimation of the emitted luminance is necessary for the objective HDR quality assessment metrics. In order to understand the effects of display rendering on the quality perception, an accurate HDR frame reproduction algorithm was developed, and a subjective experiment was conducted to analyze the impact of different display renderings on subjective and objective HDR quality evaluation. Additionally, in order to understand the impact of color with the increased brightness of the HDR displays, the effects of different color spaces on the HDR video compression performance were also analyzed in another subjective study. Another challenge is to estimate the quality of HDR content objectively, using computers and algorithms. In order to address this challenge, the thesis proceeds with the performance evaluation of full-reference (FR) HDR image quality metrics. HDR images have a larger brightness range and higher contrast values. Since most of the image quality metrics are developed for SDR images, they need to be adapted in order to estimate the quality of HDR images. Different adaptation methods were used for SDR metrics, and they were compared with the existing image quality metrics developed exclusively for HDR images. Moreover, we propose a new method for the evaluation of metric discriminability based ona novel classification approach. Motivated by the need to fuse several different quality databases, in the third part of the thesis, we compare subjective quality scores acquired by using different subjective test methodologies. Subjective quality assessment is regarded as the most effective and reliable way of obtaining “ground-truth” quality scores for the selected stimuli, and the obtained mean opinion scores (MOS) are the values to which generally objective metrics are trained to match. In fact, strong discrepancies can easily be notified across databases when different multimedia quality databases are considered. In order to understand the relationship between the quality values acquired using different methodologies, the relationship between MOS values and pairwise comparisons (PC) scaling results were compared. For this purpose, a series of experiments were conducted using double stimulus impairment scale (DSIS) and pairwise comparisons subjective methodologies. We propose to include cross-content comparisons in the PC experiments in order to improve scaling performance and reduce cross-content variance as well as confidence intervals. The scaled PC scores can also be used for subjective multimedia quality assessment scenarios other than HDR
Ševčík, Martin. "Modelování vlastností modelu HVS v Matlabu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217656.
Повний текст джерелаDalasari, Venkata Gopi Krishna, and Sri Krishna Jayanty. "Low Light Video Enhancement along with Objective and Subjective Quality Assessment." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13500.
Повний текст джерелаGuo, Jinjiang. "Contributions to objective and subjective visual quality assessment of 3d models." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI099.
Повний текст джерелаIn computer graphics realm, three-dimensional graphical data, generally represented by triangular meshes, have become commonplace, and are deployed in a variety of application processes (e.g., smoothing, compression, remeshing, simplification, rendering, etc.). However, these processes inevitably introduce artifacts, altering the visual quality of the rendered 3D data. Thus, in order to perceptually drive the processing algorithms, there is an increasing need for efficient and effective subjective and objective visual quality assessments to evaluate and predict the visual artifacts. In this thesis, we first present a comprehensive survey on different sources of artifacts in digital graphics, and current objective and subjective visual quality assessments of the artifacts. Then, we introduce a newly designed subjective quality study based on evaluations of the local visibility of geometric artifacts, in which observers were asked to mark areas of 3D meshes that contain noticeable distortions. The collected perceived distortion maps are used to illustrate several perceptual functionalities of the human visual system (HVS), and serve as ground-truth to evaluate the performances of well-known geometric attributes and metrics for predicting the local visibility of distortions. Our second study aims to evaluate the visual quality of texture mapped 3D model subjectively and objectively. To achieve these goals, we introduced 136 processed models with both geometric and texture distortions, conducted a paired-comparison subjective experiment, and invited 101 subjects to evaluate the visual qualities of the models under two rendering protocols. Driven by the collected subjective opinions, we propose two objective visual quality metrics for textured meshes, relying on the optimal combinations of geometry and texture quality measures. These proposed perceptual metrics outperform their counterparts in term of the correlation with the human judgment
Shahid, Muhammad. "Methods for Objective and Subjective Video Quality Assessment and for Speech Enhancement." Doctoral thesis, Blekinge Tekniska Högskola [bth.se], Faculty of Engineering - Department of Applied Signal Processing, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00603.
Повний текст джерелаKhaustova, Darya. "Objective assessment of stereoscopic video quality of 3DTV." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S021/document.
Повний текст джерелаThe minimum requirement for any 3D (stereoscopic images) system is to guarantee visual comfort of viewers. Visual comfort is one of the three primary perceptual attributes of 3D QoE, which can be linked directly with technical parameters of a 3D system. Therefore, the goal of this thesis is to characterize objectively the impact of these parameters on human perception for stereoscopic quality monitoring. The first part of the thesis investigates whether visual attention of the viewers should be considered when designing an objective 3D quality metrics. First, the visual attention in 2D and 3D is compared using simple test patterns. The conclusions of this first experiment are validated using complex stimuli with crossed and uncrossed disparities. In addition, we explore the impact of visual discomfort caused by excessive disparities on visual attention. The second part of the thesis is dedicated to the design of an objective model of 3D video QoE, which is based on human perceptual thresholds and acceptability level. Additionally we explore the possibility to use the proposed model as a new subjective scale. For the validation of proposed model, subjective experiments with fully controlled still and moving stereoscopic images with different types of view asymmetries are conducted. The performance is evaluated by comparing objective predictions with subjective scores for various levels of view discrepancies which might provoke visual discomfort
Sahu, Amit K. "Objective assessment of image quality (OAIQ) in fluorescence-enhanced optical imaging." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1068.
Повний текст джерелаChintala, Bala Venkata Sai Sundeep. "Objective Perceptual Quality Assessment of JPEG2000 Image Coding Format Over Wireless Channel." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17785.
Повний текст джерелаReilly, Andrew James. "Uniform framework for the objective assessment and optimisation of radiotherapy image quality." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5589.
Повний текст джерелаКниги з теми "Subjective and Objective Image Quality Assessment"
Lorsakul, Auranuch. Objective Assessment of Image Quality: Extension of Numerical Observer Models to Multidimensional Medical Imaging Studies. [New York, N.Y.?]: [publisher not identified], 2015.
Знайти повний текст джерелаSicari, Rosa, Edyta Płońska-Gościniak, and Jorge Lowenstein. Stress echocardiography: image acquisition and modalities. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198726012.003.0013.
Повний текст джерелаCarrión, Victor G., John A. Turner, and Carl F. Weems. Sleep. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190201968.003.0005.
Повний текст джерелаWilliams, Jerry R. Diagnostic radiology equipment. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199655212.003.0012.
Повний текст джерелаЧастини книг з теми "Subjective and Objective Image Quality Assessment"
Barkowsky, Marcus, Kjell Brunnström, Touradj Ebrahimi, Lina Karam, Pierre Lebreton, Patrick Le Callet, Andrew Perkis, et al. "Subjective and Objective Visual Quality Assessment in the Context of Stereoscopic 3D-TV." In 3D-TV System with Depth-Image-Based Rendering, 413–37. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-9964-1_14.
Повний текст джерелаKowalik-Urbaniak, Ilona A., Jane Castelli, Nasim Hemmati, David Koff, Nadine Smolarski-Koff, Edward R. Vrscay, Jiheng Wang, and Zhou Wang. "Modelling of Subjective Radiological Assessments with Objective Image Quality Measures of Brain and Body CT Images." In Lecture Notes in Computer Science, 3–13. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20801-5_1.
Повний текст джерелаCheeseman, Alison K., Ilona A. Kowalik-Urbaniak, and Edward R. Vrscay. "Objective Image Quality Measures of Degradation in Compressed Natural Images and their Comparison with Subjective Assessments." In Lecture Notes in Computer Science, 163–72. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41501-7_19.
Повний текст джерелаLewandowska, Anna. "Subjective Image Quality Assessment Optimization." In Advances in Intelligent Systems and Computing, 171–78. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47274-4_20.
Повний текст джерелаPramerdorfer, Christopher, and Martin Kampel. "Deep Objective Image Quality Assessment." In Computer Analysis of Images and Patterns, 127–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64698-5_12.
Повний текст джерелаDing, Yong. "Subjective Ratings and Image Quality Databases." In Visual Quality Assessment for Natural and Medical Image, 5–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56497-4_2.
Повний текст джерелаXu, Jiahua, Chaoyi Lin, Wei Zhou, and Zhibo Chen. "Subjective Quality Assessment of Stereoscopic Omnidirectional Image." In Advances in Multimedia Information Processing – PCM 2018, 589–99. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00776-8_54.
Повний текст джерелаLandre, Victor, Marius Pedersen, and Dag Waaler. "Memory Effects in Subjective Quality Assessment of X-Ray Images." In Image Analysis, 314–25. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59129-2_27.
Повний текст джерелаZhang, Changjiang, Juan Lu, and Jinshan Wang. "Objective Quality Assessment Measurement for Typhoon Cloud Image Enhancement." In Image Analysis and Processing – ICIAP 2009, 767–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04146-4_82.
Повний текст джерелаKoumaras, Harilaos G. "Objective and Subjective Assessment Methods of Video Quality in Multimedia Broadcasting." In Mobile Multimedia Broadcasting Standards, 417–34. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-78263-8_14.
Повний текст джерелаТези доповідей конференцій з теми "Subjective and Objective Image Quality Assessment"
Queluz, Maria Paula, Francisco Lopes, João Ascenso, and António Rodrigues. "Subjective and objective quality assessment of omnidirectional video." In Applications of Digital Image Processing XLI, edited by Andrew G. Tescher. SPIE, 2018. http://dx.doi.org/10.1117/12.2321679.
Повний текст джерелаBhargava, Chitresh, and Nidhi Verma. "Improved subjective and objective image quality assessment of JPEG image." In 2014 International Conference on Information Communication and Embedded Systems (ICICES). IEEE, 2014. http://dx.doi.org/10.1109/icices.2014.7033994.
Повний текст джерелаHou, Limin, Weiqi Wu, Shuang Yang, Tao Yang, and Xinpeng Zhang. "Subjective and objective quality assessment of re-sampling audio." In 2012 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2012. http://dx.doi.org/10.1109/icalip.2012.6376634.
Повний текст джерелаGu, Ke, Guangtao Zhai, Xiaokang Yang, Wenjun Zhang, and Min Liu. "Subjective and objective quality assessment for images with contrast change." In 2013 20th IEEE International Conference on Image Processing (ICIP). IEEE, 2013. http://dx.doi.org/10.1109/icip.2013.6738079.
Повний текст джерелаWang, Xu, Lei Cao, Yingying Zhu, Yun Zhang, Jianmin Jiang, and Sam Kwong. "Study of subjective and objective quality assessment for screen content images." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296381.
Повний текст джерелаTrioux, Anthony, Giuseppe Valenzise, Marco Cagnazzo, Michel Kieffer, Francois-Xavier Coudoux, Patrick Corlay, and Mohamed Gharbi. "Subjective and Objective Quality Assessment of the SoftCast Video Transmission Scheme." In 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2020. http://dx.doi.org/10.1109/vcip49819.2020.9301778.
Повний текст джерелаChaabouni, A., Y. Gaudeau, J. Lambert, J. M. Moureaux, and P. Gallet. "Subjective and objective quality assessment for H264 compressed medical video sequences." In 2014 4th International Conference on Image Processing Theory, Tools and Applications (IPTA). IEEE, 2014. http://dx.doi.org/10.1109/ipta.2014.7001922.
Повний текст джерелаWang, Anyang, Guangtao Zhai, Yuanchun Chen, Zhaohui Che, and Xiaokang Yang. "Subjective and objective quality assessment for color changed images." In 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). IEEE, 2017. http://dx.doi.org/10.1109/bmsb.2017.7986169.
Повний текст джерелаChen, Qi, Fang Liu, Huiyu Duan, Yao Wang, Xiongkuo Min, Yan Zhou, and Guangtao Zhai. "MRIQA: Subjective Method and Objective Model for Magnetic Resonance Image Quality Assessment." In 2022 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2022. http://dx.doi.org/10.1109/vcip56404.2022.10008885.
Повний текст джерелаEbenezer, Joshua P., Yixu Chen, Yongjun Wu, Hai Wei, and Sriram Sethuraman. "Subjective and Objective Quality Assessment of High-Motion Sports Videos at Low-Bitrates." In 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022. http://dx.doi.org/10.1109/icip46576.2022.9897837.
Повний текст джерелаЗвіти організацій з теми "Subjective and Objective Image Quality Assessment"
Mizrach, Amos, Sydney L. Spahr, Ephraim Maltz, Michael R. Murphy, Zeev Schmilovitch, Jan E. Novakofski, Uri M. Peiper, et al. Ultrasonic Body Condition Measurements for Computerized Dairy Management Systems. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568109.bard.
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