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Journal articles on the topic 'Color space conversion'

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Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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1

Cao, Cong Jun, and Qiang Jun Liu. "Study on Color Space Conversion Based on RBF Neural Network." Advanced Materials Research 174 (December 2010): 28–31. http://dx.doi.org/10.4028/www.scientific.net/amr.174.28.

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The conversions of color spaces are core techniques of modern ICC color management and the study of color space conversion algorithm between L*a*b* and CMYK is valuable both in theory and in application. In this paper, firstly ECI2002 standard color target data are uniformly selected, including modeling data and testing data; secondly the models of color space conversions from CMYK to L*a*b* and from L*a*b* to CMYK are built based on Radial Basis Function (RBF) neural network; finally the precision of the models are evaluated. This research indicates that the RBF neural network is suitable for the color space conversions between CMYK and L*a*b*. The models’ building processes are simpler and more convenient; the network has fast training speed and good results. With the improvement of the modeling method, this method for color space conversion will have a broader application.

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2

Le, Hoang, Mahmoud Afifi, and Michael S. Brown. "Improving Color Space Conversion for Camera-Captured Images via Wide-Gamut Metadata." Color and Imaging Conference 2020, no. 28 (November 4, 2020): 193–98. http://dx.doi.org/10.2352/issn.2169-2629.2020.28.30.

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Color space conversion is the process of converting color values in an image from one color space to another. Color space conversion is challenging because different color spaces have different sized gamuts. For example, when converting an image encoded in a medium-sized color gamut (e.g., AdobeRGB or Display-P3) to a small color gamut (e.g., sRGB), color values may need to be compressed in a many-to-one manner (i.e., multiple colors in the source gamut will map to a single color in the target gamut). If we try to convert this sRGB-encoded image back to a wider gamut color encoding, it can be challenging to recover the original colors due to the color fidelity loss. We propose a method to address this problem by embedding wide-gamut metadata inside saved images captured by a camera. Our key insight is that in the camera hardware, a captured image is converted to an intermediate wide-gamut color space (i.e., ProPhoto) as part of the processing pipeline. This wide-gamut image representation is then saved to a display color space and saved in an image format such as JPEG or HEIC. Our method proposes to include a small sub-sampling of the color values from the ProPhoto image state in the camera to the final saved JPEG/HEIC image. We demonstrate that having this additional wide-gamut metadata available during color space conversion greatly assists in constructing a color mapping function to convert between color spaces. Our experiments show our metadata-assisted color mapping method provides a notable improvement (up to 60% in terms of E) over conventional color space methods using perceptual rendering intent. In addition, we show how to extend our approach to perform adaptive color space conversion based spatially over the image for additional improvements.

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Pearlstein, Larry, Alexander Benasutti, Skyler Maxwell, Matthew Kilcher, Jake Bezold, and Warren Seto. "Retrieval of Color Space Conversion Matrix via Convolutional Neural Network." International Journal of Machine Learning and Computing 9, no. 4 (August 2019): 393–400. http://dx.doi.org/10.18178/ijmlc.2019.9.4.816.

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4

Jing, Liang. "Design and Realization of Animation Composition and Tone Space Conversion Algorithm." Complexity 2021 (April 22, 2021): 1–11. http://dx.doi.org/10.1155/2021/5579547.

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In recent years, with the development of society and the rapid development of the animation industry, people are paying more and more attention to and requirements for animation production. As an indispensable part of animation production, picture composition plays a major role in animation production. It can give full play to the application of color matching and light and shadow design and enhance the depth and space of the animation screen. Tone space conversion refers to the conversion or representation of color data in one color space into corresponding data in another color space. Its purpose is to distinguish and process color components such as hue and saturation in an image. This article first introduces the domestic and foreign research status of digital image preprocessing and analyzes the basic principles of several color space conversions in detail. Then, several color space conversion algorithms are studied, and the performance of the algorithms is compared and analyzed. The paper focuses on the hardware implementation and optimization of the algorithm for converting RGB color space into HSI color space to meet the real-time requirements. This article focuses on the mutual conversion between the RGB tone space and the HSI tone space and describes in detail how each color component in the HSI tone space is converted from the three RGB color components from a geometric perspective, and then the conversion is derived, and several general conversion methods of RGB to HSI tone space are introduced; two conversion methods of geometric derivation method and standard modulus algorithm are implemented in the software, and the comparison verification is carried out, and the comparison is made from the perspective of hardware implementation. The pros and cons of the two methods are discussed. Finally, the paper summarizes the shortcomings in the design and proposes further research directions in the future.

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Alonso Pérez, M. A., and J. J. Báez Rojas. "Conversion from n bands color space to HSI n color space." Optical Review 16, no. 2 (March 2009): 91–98. http://dx.doi.org/10.1007/s10043-009-0016-5.

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6

Li, Xin Wu. "Research on Color Space Conversion Model between XYZ and RGB." Key Engineering Materials 428-429 (January 2010): 466–69. http://dx.doi.org/10.4028/www.scientific.net/kem.428-429.466.

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Color space conversion for color digital camera is a key and difficult technique in the color reproduction information optics. A new color space conversion model based on subsectional fitting to correct color conversion error camera image is presented. First, color error sources and color rendering mechanism are analyzed in theory; then the paper takes standard color target for experimental sample and substitutes color blocks in color shade district for complete color space to solve the difficulties of experimental color blocks selecting; third the model uses subsectional fitting algorithm to built three dimension color conversion curve to correct color conversion error; Finally the experimental results show that the model can color space conversion accuracy of color digital camera and can be used in color conversion for digital camera practically.

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7

Seo, Jong Wan, and Myung Chul Shin. "Fast and Accurate Color Space Conversion Matrix." Key Engineering Materials 321-323 (October 2006): 1297–300. http://dx.doi.org/10.4028/www.scientific.net/kem.321-323.1297.

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A color space used to create color on a computer monitor or a television screen is RGB color space. However, RGB color space is strongly related to each other, therefore RGB color space is inadequate for adjustment of brightness or contrast. Moreover RGB color space is not suitable for pattern recognition. For this reason, it is needed that color space conversion from RGB to YIQ, YUV or YCrCb. The color space conversion matrix consists of 3 by 3 matrix element that is represented by floating point numbers. However RGB or YUV color space is in integer domain. Therefore these transform lead to lose the least significant bit (LSB) of color space. We propose the simple and fast reversible transform matrix. No lose the least significant bit (LSB) and not required multiplication but shift and addition that provides for real time conversion of huge image.

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8

Hua, Liang, Zhen Tao Zhou, Ji Yang, Hao Feng, Li Jun Ding, and Ju Ping Gu. "Fuzzy Enhancement Method for Color Medical Images Based on Color Space Conversion." Applied Mechanics and Materials 380-384 (August 2013): 3706–9. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3706.

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A new fuzzy enhancement method is put forward in the paper combining with Young-Helmholtz (Y-H) color space and fuzzy set theory. Color images with RGB tri-channels are transformed into Y-H color space by using Greaves transformation method. The colors image could be decomposed into chromaticity numbers matrix and intensity numbers matrix. The intensity numbers matrix is processed by using fuzzy enhancement arithmetic, while chromaticity numbers matrix keeps invariant. The primary chromaticity numbers matrix and enhanced intensity numbers matrix are processed by using Y-H inverse transformation. The method put forward in the paper have characteristics of efficiency, convenience and high speed. The method can achieve enhancement for color medical images without changing hue and saturation.

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9

Bi, Zhicheng, and Peng Cao. "Color space conversion algorithm and comparison study." Journal of Physics: Conference Series 1976, no. 1 (July 1, 2021): 012008. http://dx.doi.org/10.1088/1742-6596/1976/1/012008.

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10

Amara, Mohamed, Fabien Mandorlo, Romain Couderc, Félix Gerenton, and Mustapha Lemiti. "Temperature and color management of silicon solar cells for building integrated photovoltaic." EPJ Photovoltaics 9 (2018): 1. http://dx.doi.org/10.1051/epjpv/2017008.

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Color management of integrated photovoltaics must meet two criteria of performance: provide maximum conversion efficiency and allow getting the chosen colors with an appropriate brightness, more particularly when using side by side solar cells of different colors. As the cooling conditions are not necessarily optimal, we need to take into account the influence of the heat transfer and temperature. In this article, we focus on the color space and brightness achieved by varying the antireflective properties of flat silicon solar cells. We demonstrate that taking into account the thermal effects allows freely choosing the color and adapting the brightness with a small impact on the conversion efficiency, except for dark blue solar cells. This behavior is especially true when heat exchange by convection is low. Our optical simulations show that the perceived color, for single layer ARC, is not varying with the position of the observer, whatever the chosen color. The use of a double layer ARC adds flexibility to tune the wanted color since the color space is greatly increased in the green and yellow directions. Last, choosing the accurate material allows both bright colors and high conversion efficiency at the same time.

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Zhi, Chuan, Ling Hua Guo, Mei Yun Zhang, and Yi Shi. "Research on Dynamic Subspace Divided BP Neural Network Identification Method of Color Space Transform Model." Advanced Materials Research 174 (December 2010): 97–100. http://dx.doi.org/10.4028/www.scientific.net/amr.174.97.

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In order to improve the precision for BP neural network model color space conversion, this paper takes RGB color space and CIE L*a*b* color space as an example. Based on the input value, the color space is dynamically divided into many subspaces. To adopt the BP neural network in the subspace can effectively avoiding the local optimum of BP neural network in the whole color space and greatly improving the color space conversion precision.

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Sun, Bangyong, Han Liu, Shisheng Zhou, and Wenli Li. "Evaluating the Performance of Polynomial Regression Method with Different Parameters during Color Characterization." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/418651.

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The polynomial regression method is employed to calculate the relationship of device color space and CIE color space for color characterization, and the performance of different expressions with specific parameters is evaluated. Firstly, the polynomial equation for color conversion is established and the computation of polynomial coefficients is analysed. And then different forms of polynomial equations are used to calculate the RGB and CMYK’s CIE color values, while the corresponding color errors are compared. At last, an optimal polynomial expression is obtained by analysing several related parameters during color conversion, including polynomial numbers, the degree of polynomial terms, the selection of CIE visual spaces, and the linearization.

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13

Zhang, Hao Ran, Wen Ping Ren, Wen Long Yin, and Shao Feng Chen. "FPGA-Based Bayer to YCbCr Color Space Design." Applied Mechanics and Materials 696 (November 2014): 105–9. http://dx.doi.org/10.4028/www.scientific.net/amm.696.105.

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Because of the powerful data processing ability of FPGA, the fast interpolation algorithm is used for Bayer format data which comes from CMOS sensor MT9M011 to convert to RGB image format. In the RGB color space to YCbCr space conversion stage,using color space conversion formula, combined with the characteristics of FPGA, realize the conversion of RGB to YCbCr. Finally, correctness is verified by the experimental results which use SignalTap II embedded logic analyzer.

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Zhi, Chuan, Zhi Jian Li, and Yi Shi. "Research on Robustness of Color Device Characteristic Methods Based on Artificial Intelligence." Applied Mechanics and Materials 262 (December 2012): 65–68. http://dx.doi.org/10.4028/www.scientific.net/amm.262.65.

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The nature of device color characteristic methods is the mutual conversion of device-dependent color space and device-independent color space. This paper does the comparative study on the robustness of some color space conversion methods which are based on fuzzy control, dynamic subspace divided BP neural network identification method, and fuzzy and neural identification method, by defining the robustness of color space conversion model and evaluation method. The result shows that the device color characteristic methods which are based on fuzzy and neural identification method can make the feature of BP neural network combine with fuzzy control to greatly improve the robustness of model.

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15

Liang Hua, Zhentao Zhou, Hao Feng, Lijun Ding, Juping Gu, and Xiao Wu. "Method of Color Medical Image Enhancement Based on Color Space Conversion." International Journal of Digital Content Technology and its Applications 7, no. 1 (January 15, 2013): 687–95. http://dx.doi.org/10.4156/jdcta.vol7.issue1.78.

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Hasche, Eberhard, Oliver Karaschewski, and Reiner Creutzburg. "Using ACES Look Modification Transforms (LMTs) in VFX Environments – Part 2: Gamut Mapping." Electronic Imaging 2021, no. 3 (June 18, 2021): 108–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.3.mobmu-108.

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In modern moving image production pipelines, it is unavoidable to move the footage through different color spaces. Unfortunately, these color spaces exhibit color gamuts of various sizes. The most common problem is converting the cameras’ widegamut color spaces to the smaller gamuts of the display devices (cinema projector, broadcast monitor, computer display). So it is necessary to scale down the scene-referred footage to the gamut of the display using tone mapping functions [34].In a cinema production pipeline, ACES is widely used as the predominant color system. The all-color compassing ACES AP0 primaries are defined inside the system in a general way. However, when implementing visual effects and performing a color grade, the more usable ACES AP1 primaries are in use. When recording highly saturated bright colors, color values are often outside the target color space. This results in negative color values, which are hard to address inside a color pipeline. "Users of ACES are experiencing problems with clipping of colors and the resulting artifacts (loss of texture, intensification of color fringes). This clipping occurs at two stages in the pipeline: <list list-type="simple"> <list-item>- Conversion from camera raw RGB or from the manufacturer’s encoding space into ACES AP0</list-item> <list-item>- Conversion from ACES AP0 into the working color space ACES AP1" [1]</list-item> </list>The ACES community established a Gamut Mapping Virtual Working Group (VWG) to address these problems. The group’s scope is to propose a suitable gamut mapping/compression algorithm. This algorithm should perform well with wide-gamut, high dynamic range, scene-referred content. Furthermore, it should also be robust and invertible. This paper tests the behavior of the published GamutCompressor when applied to in- and out-ofgamut imagery and provides suggestions for application implementation. The tests are executed in The Foundry’s Nuke [2].

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Azetsu, Tadahiro, and Noriaki Suetake. "Chroma Enhancement in CIELAB Color Space Using a Lookup Table." Designs 5, no. 2 (May 14, 2021): 32. http://dx.doi.org/10.3390/designs5020032.

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In this study, we present a method of chroma enhancement in the CIELAB color space and compare it with that in the RGB color space. Color image enhancement using the CIELAB color space has the disadvantage that the color gamut problem occurs because the conversion to the RGB color space is necessary to display the image. However, since the CIELAB color space is based on human visual perception, the quality of the resulting images is expected to be higher than that of the RGB color space. In the method using the CIELAB color space, we introduce a lookup table to reduce the calculation costs. Experiments comparing image enhancement results obtained from two color spaces are performed using several digital images.

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18

Yamada, Shota, Tomoyoshi Shimobaba, Takashi Kakue, and Tomoyoshi Ito. "Full-color computer-generated hologram using wavelet transform and color space conversion." Optics Express 27, no. 6 (March 6, 2019): 8153. http://dx.doi.org/10.1364/oe.27.008153.

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19

Min, Kim, Song, and Kim. "A G-Fresnel Optical Device and Image Processing Based Miniature Spectrometer for Mechanoluminescence Sensor Applications." Sensors 19, no. 16 (August 12, 2019): 3528. http://dx.doi.org/10.3390/s19163528.

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This paper presents a miniature spectrometer fabricated based on a G-Fresnel optical device (i.e., diffraction grating and Fresnel lens) and operated by an image-processing algorithm, with an emphasis on the color space conversion in the range of visible light. The miniature spectrometer will be cost-effective and consists of a compact G-Fresnel optical device, which diffuses mixed visible light into the spectral image and a μ-processor platform embedded with an image-processing algorithm. The RGB color space commonly used in the image signal from a complementary metal–oxide–semiconductor (CMOS)-type image sensor is converted into the HSV color space, which is one of the most common methods to express color as a numeric value using hue (H), saturation (S), and value (V) via the color space conversion algorithm. Because the HSV color space has the advantages of expressing not only the three primary colors of light as the H but also its intensity as the V, it was possible to obtain both the wavelength and intensity information of the visible light from its spectral image. This miniature spectrometer yielded nonlinear sensitivity of hue in terms of wavelength. In this study, we introduce the potential of the G-Fresnel optical device, which is a miniature spectrometer, and demonstrated by measurement of the mechanoluminescence (ML) spectrum as a proof of concept.

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Chen, Ching Yi, Ching Han Chen, Chih Hao Ma, and Po Yi Wu. "An Efficient Genetic Encoding Scheme for Multiplierless Color Space Converter Design." Applied Mechanics and Materials 284-287 (January 2013): 3015–19. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3015.

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Color space conversion has become a very important role in image and video processing systems. To speed up some processing processes, many communication and multimedia video compression schemes use luminance-chrominance type color spaces, such as YCbCr or YUV, making a mechanism for converting between different formats necessary. Therefore, techniques which efficiently implement this conversion are desired. For the recent years, a new field of research called Evolvable Hardware (EHW) has emerged which combines aspects of evolutionary computation with hardware design and synthesis. It is a new scheme inspired by natural evolution, for automatic design of hardware systems. This paper presents a novel evolutionary approach for efficient implementation of a RGB to YCbCr color space converter suitable for Field Programmable Gate Array (FPGAs) and VLSI. In the proposed method, we use the genetic algorithm to automatically evolve the multiplierless architecture of the color space converter. The architecture employs only a few shift and addition operations to replace the complex multiplications. The experimental results represent that the performance of implemented architecture is good at RGB to YCbCr color space converting, and it also has the advantages of high-speed, low-complexity, and low-area.

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Chu, Chen, Jian Wang, Sen Ke Hou, Qi Lv, Guo Qiang Ma, and Xiao Yong Ji. "A Comparative Study of Color Space Conversion on Homogeneous and Heterogeneous Multicore." Applied Mechanics and Materials 519-520 (February 2014): 724–28. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.724.

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Color space conversion (CSC) is an important kernel in the area of image and video processing applications including video compression. As a matrix math, this operation consumes up to 40% of processing time of a highly optimized decoder. Therefore, techniques which efficiently implement this conversion are desired. Multicore processors provide an opportunity to increase the performance of CSC by exploiting data parallelism. In this paper, we present three novel approaches for efficient implementation of color space conversion suitable for homogeneous and heterogeneous multicore. We compare the performance of color space conversion on a variety of platforms including OpenMP running on homogeneous multicore CPUs, CUDA with NVIDIA GPUs and OpenCL running on both NVIDIA and ATI GPUs. Our experimental results show that the speedup of3×, 17×and15×can been obtained, respectively.

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22

Lee, Dah-Jye, James K. Archibald, Yu-Chou Chang, and Christopher R. Greco. "Robust color space conversion and color distribution analysis techniques for date maturity evaluation." Journal of Food Engineering 88, no. 3 (October 2008): 364–72. http://dx.doi.org/10.1016/j.jfoodeng.2008.02.023.

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23

Ohkoba, Minoru, Tomoharu Ishikawa, Shoko Hira, Sakuichi Ohtsuka, and Miyoshi Ayama. "Analysis of Hue Circle Perception of Congenital Red-green Congenital Color Deficiencies Based on Color Vision Model." Color and Imaging Conference 2020, no. 28 (November 4, 2020): 105–8. http://dx.doi.org/10.2352/issn.2169-2629.2020.28.15.

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To investigate individual property of internal color representation of congenital red-green color-deficient observers (CDOs) and color-normal observers (CNOs) precisely, difference scaling experiment using pairs of primary colors was carried out for protans, deutans, and normal trichromats, and the results were analyzed using multi-dimensional Scaling (MDS). MDS configuration of CNOs showed circular shape similar to hue circle, whereas that of CNO showed large individual differences from circular to U- shape. Distortion index, DI, is proposed to express the shape variation of MDS configuration. All color chips were plotted in the color vision space, (L, r/g, y/b), and the MDS using a non-linear conversion from the distance in the color vision space to perceptual difference scaling was successful to obtain U-shape configuration that reflects internal color representation of CDOs.

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Ge, Yun Lu, Hui Han, Xiao Dong Sun, Sheng Pin Wang, and Sheng Yun Ji. "A Robustness Watermarking Algorithm for Digital Color Image Print-Scan Process." Applied Mechanics and Materials 333-335 (July 2013): 992–97. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.992.

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Most of watermarking algorithms are for digital grey image, which are not robust against the attacks of print-scan process, and the embedded information capacity is small. To solve these problem, a new method based on DWT transform and Walsh orthogonal transform for the print-scan process of digital color image was proposed. The method chosed the color spaces conversion from RGB to CIEL*a*b* for digital color image. The low frequency components of the DWT transform image was embed the watermark. The results show that the correlation of watermark is improved using Walsh orthogonal transform, the watermark extraction rate is high and image watermark is distinct and readable after print-scan process. And this method is robust against the various attacks of the print-scan process, such as color space conversion, image halftone, D/A conversion, A/D conversion, scaling, rotation, cropping, skew, and random noise signals.

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Wen, Long, Cheng Xu, Tao Li, and Zheng Tian. "Implementation of RGB to HSV Color Space Conversion with Xilinx System Generator." Advanced Materials Research 816-817 (September 2013): 527–34. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.527.

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The HSV (Hue, Saturation, and Value) color model is more intuitive than the RGB color model and widely used in color recognition and color space segmentation. Currently as the requirements of high processing speed and special applications need to realize RGB to HSV color space conversion, in this paper a new Field Programmable Gate Array (FPGA) architecture named RGB2HSV module was developed via an accurate and visible FPGA implementation method in use of Xilinx System Generator (XSG). XSG is a design tool in Simulink of MATLAB which accelerates design by providing access to highly parameterized intellectual blockset for Xilinx FPGA. In this paper simulation test images were used to measure the deviation and the time consume by the RGB2HSV module and relevant C program. Experiment shows that the maximum frequency can reach 121.433MHz and lower deviation was achieved in Xilinx Zynq xc7z020 device. The full-pipelined and parallel RGB2HSV module had been adapted in order to speed up the RGB to HSV color space conversion and took as much as 87% less than that of C program in our experiment.

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Li, Hui Yong, Hong Xu Jiang, Ping Zhang, Han Qing Li, and Qian Cao. "Efficient RGB to YCbCr Color Space Conversion for Embedded Application." Applied Mechanics and Materials 543-547 (March 2014): 2873–78. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2873.

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Modern embedded portable devices usually have to deal with large amounts of video data. Due to massive floating-point multiplications, the color space conversion is inefficient on the embedded processor. Considering the characteristics of RGB to YCbCr color space conversion, this paper proposed a strategy for truncated-based LUT Multiplier (T-LUT Multiplier). On this base, an original approach converting RGB to YCbCr is presented which employs the T-LUT Multiplier and the pipeline-based adder. Experimental results demonstrate that the proposed method can obtain maximum operating frequency of 358MHz, 3.5 times faster than the direct method. Furthermore, the power consumption is less than that of the general method approximately by 15%~27%.

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Nesam, J. Jean Jenifer, and S. Sivanantham. "Efficient half-precision floating point multiplier targeting color space conversion." Multimedia Tools and Applications 79, no. 1-2 (August 9, 2019): 89–117. http://dx.doi.org/10.1007/s11042-019-08040-y.

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Yang, Hang Jun, Jian Wang, and Xiao Yong Ji. "Accelerating Color Space Conversion Using CUDA-Enabled Graphic Processing Units." Advanced Materials Research 716 (July 2013): 505–9. http://dx.doi.org/10.4028/www.scientific.net/amr.716.505.

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Color space conversion (CSC) is an important kernel in the area of image and video processing applications including video compression. CSC is a compute-intensive time-consuming operation that consumes up to 40% of processing time of a highly optimised decoder. Several hardware and software implementations for CSC have been found. Hardware implementations can achieve a higher performance compared with software-only solutions. However, the flexibility of software solutions is desirable for various functional requirements and faster time to market. Multicore processors, especially programmable GPUs, provide an opportunity to increase the performance of CSC by exploiting data parallelism. In this paper, we present a novel approach for efficient implementation of color space conversion. The proposed approach has been implemented and verified using computed unified device architecture (CUDA) on graphics hardware. Our experiments results show that the speedup of up to17×can been obtained.

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Hiyama, Daisuke, Tomoyoshi Shimobaba, Takashi Kakue, and Tomoyoshi Ito. "Acceleration of color computer-generated hologram from RGB–D images using color space conversion." Optics Communications 340 (April 2015): 121–25. http://dx.doi.org/10.1016/j.optcom.2014.11.099.

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Cong, Dong Sheng, Liu Ping Feng, and Hui Hui Lyu. "Research on the Color Mixingand Embedding of Infrared Detectable Watermark Studies." Applied Mechanics and Materials 713-715 (January 2015): 1872–76. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.1872.

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In order to study and broaden theapplication ofinfrared watermark, use the methods of gray componentreplacementto replace some or all of the black ink, get another replacement color. So that make the two colors has same visual effectin the visible light.However,thepresence of differences colors on the content of black ink. UseInfrared detection equipment to analysis two colors findthey existed differences in gray space.Under Infrared can be distinguished.Experiments usingcolor space conversion to achieve GCRalgorithmsand two color using print presses achieve infrared watermark embedding, then get a watermark graphic by infrared detection devices.

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Wu, Jian Sheng, Bin Zhang, and Yun Ling Gao. "An Effective Flame Segmentation Method Based on Ohta Color Space." Advanced Materials Research 485 (February 2012): 7–11. http://dx.doi.org/10.4028/www.scientific.net/amr.485.7.

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A new fire segmentation method is proposed, which based on OHTA color model and Otsu method. Through this method we can accurately split flame in different weather conditions and different environmental conditions outdoor. The flame can be extracted completely. The method takes advantage of the flame image color space, color information and spatial characteristics of the different complementary color and provides a new idea for the extraction of flame image. This is an efficient flame segmentation algorithm, and time complexity is low. And the conversion from the RGB color space to OHTA color space is linear. It can achieve flame object segmentation from video streams in Video-based flame detection system

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Shimobaba, Tomoyoshi, Yuki Nagahama, Takashi Kakue, Naoki Takada, Naohisa Okada, Yutaka Endo, Ryuji Hirayama, Daisuke Hiyama, and Tomoyoshi Ito. "Calculation reduction method for color digital holography and computer-generated hologram using color space conversion." Optical Engineering 53, no. 2 (February 28, 2014): 024108. http://dx.doi.org/10.1117/1.oe.53.2.024108.

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Nagahama, Yuki, Tomoyoshi Shimobaba, Takashi Kakue, and Tomoyoshi Ito. "Calculation Reduction Method for Color Holography Using Color Space Conversion; Application to iterative optimization algorithm." Journal of The Institute of Image Information and Television Engineers 68, no. 4 (2014): J162—J164. http://dx.doi.org/10.3169/itej.68.j162.

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Shimobaba, Tomoyoshi, Michał Makowski, Yuki Nagahama, Yutaka Endo, Ryuji Hirayama, Daisuke Hiyama, Satoki Hasegawa, et al. "Color computer-generated hologram generation using the random phase-free method and color space conversion." Applied Optics 55, no. 15 (May 18, 2016): 4159. http://dx.doi.org/10.1364/ao.55.004159.

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Journal, Baghdad Science. "Image data compression by using multiwavelete for color image." Baghdad Science Journal 3, no. 4 (December 3, 2006): 722–28. http://dx.doi.org/10.21123/bsj.3.4.722-728.

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There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja

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CAO, Cong-jun, Ming-quan ZHOU, and Yi KANG. "Study on color space conversion from CMYK to L* a* b*." Journal of Computer Applications 28, no. 1 (October 14, 2008): 165–67. http://dx.doi.org/10.3724/sp.j.1087.2008.00165.

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Tymochko, Oleksandr, Volodymyr Larin, Maksym Kolmykov, Oleksander Timochko, and Vladislava Pavlenko. "RESEARCH OF IMAGES FILTRATION METHODS IN COMPUTER SYSTEMS." Advanced Information Systems 5, no. 1 (June 22, 2021): 93–99. http://dx.doi.org/10.20998/2522-9052.2021.1.13.

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It is known that human eyes are less sensitive to color, than to their brightness. In the RGB color space, all three components are considered equally important, and they are usually stored with the same resolution. However, you can display a color image more efficiently, separating the brightness from color information and presenting it with a higher resolution than color. RGB space is well suited for computer graphics, because it uses these three components for color formation. However, RGB space is not very effective when it comes to real images. The fact is that to save the color of an image, you need to know and store all three components of the RGB, and if one of them is missing, it will greatly distort the visual image representation. Also, when processing images in RGB space, it is not always convenient to perform any pixel conversion, because, in this case, it will be necessary to list all three values of the RGB component and write back. This greatly reduces the performance of various image processing algorithms. For these and other reasons, many video standards use brightness and two signals that carry information about the red and blue components of the signal, as a color model other than RGB. The most famous among such spaces is YCbCr.

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Chen, Ching-Yi, Ching-Han Chen, Chih-Hao Ma, and Po-Yi Wu. "AUTOMATIC DESIGN OF SHIFT-AND-ADD BASED COLOR SPACE CONVERTER USING A GENETIC ALGORITHM." Transactions of the Canadian Society for Mechanical Engineering 37, no. 3 (September 2013): 959–70. http://dx.doi.org/10.1139/tcsme-2013-0082.

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The main purpose of this paper is to investigate a novel design method using a genetic algorithm (GA) to automatically evolve the multiplierless CSC circuit architecture. In order to demonstrate the effectiveness of the described design method, several test images are adopted respectively to perform RGB to YCbCr color conversion experiment. The experimental results represent that the performance of the implemented hardware architecture is good when carrying out color space conversion from RGB to YCbCr. It also has the advantage of being high-speed, low-complexity, and low-area.

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Deng, Li, Sui-Huai Yu, Wen-Jun Wang, Jun-Xuan Chen, and Guo-Chang Liu. "Color Image Evaluation for Small Space Based on FA and GEP." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/863150.

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Aiming at the problem that color image is difficult to quantify, this paper proposes an evaluation method of color image for small space based on factor analysis (FA) and gene expression programming (GEP) and constructs a correlation model between color image factors and comprehensive color image. The basic color samples of small space and color images are evaluated by semantic differential method (SD method), color image factors are selected via dimension reduction in FA, factor score function is established, and by combining the entropy weight method to determine each factor weights then the comprehensive color image score is calculated finally. The best fitting function between color image factors and comprehensive color image is obtained by GEP algorithm, which can predict the users’ color image values. A color image evaluation system for small space is developed based on this model. The color evaluation of a control room on AC frequency conversion rig is taken as an example, verifying the effectiveness of the proposed method. It also can assist the designers in other color designs and provide a fast evaluation tool for testing users’ color image.

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Saptariani, Trini, Sarifudin Madenda, Ernastuti Ernastuti, and Widya Silfianti. "Accelerating Compression Time of the standard JPEG by Employing The Quantized YCbCr Color Space Algorithm." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4343. http://dx.doi.org/10.11591/ijece.v8i6.pp4343-4351.

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In this paper, we propose a quantized YCbCr color space (QYCbCr) technique which is employed in standard JPEG. The objective of this work is to accelerate computational time of the standard JPEG image compression algorithm. This is a development of the standard JPEG which is named QYCBCr algorithm. It merges two processes i.e., YCbCr color space conversion and Q quantization in which in the standar JPEG they were performed separately. The merger forms a new single integrated process of color conversion which is employed prior to DCT process by subsequently eliminating the quantization process. The equation formula of QYCbCr color coversion is built based on the chrominance and luminance properties of the human visual system which derived from quatization matrices. Experiment results performed on images of different sizes show that the computational running time of QYCbCr algorithm gives 4 up to 8 times faster than JPEG standard, and also provides higher compression ratio and better image quality.

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Chen, Ching Yi, and Chi Chiang Ko. "Designing FIRA Medium-Sized Soccer Robot Vision System Using Particle Swarm Optimization." Applied Mechanics and Materials 764-765 (May 2015): 675–79. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.675.

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Enabling FIRA medium-sized soccer robots to recognize target objects according to color information requires that competing teams manually set the range of colors according to ambient lighting conditions prior to games. This color information is used to differentiate features of target objects, such as the ball, the goals, and the field. Constructing a color-feature model such as this is extremely time-consuming and the resulting model is unable to adapt dynamically to changes in lighting conditions. This study applied a look-up table method to execute RGB-HSV color space conversion to accelerate video processing. A particle swarm optimization (PSO) scheme was developed to detect the color-feature parameters of the target objects in the HSV color space. This enables the automatic completion of color-feature modeling and the construction of the knowledge model required by the robot for object recognition. Experiment results demonstrate that the proposed method is capable of enhancing the robustness of the robot vision system in determining changes in lighting conditions. In addition, the manpower and time required to set robot parameters prior to games were reduced significantly.

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Karaimer, Hakki Can, and Michael S. Brown. "Beyond raw-RGB and sRGB: Advocating Access to a Colorimetric Image State." Color and Imaging Conference 2019, no. 1 (October 21, 2019): 86–90. http://dx.doi.org/10.2352/issn.2169-2629.2019.27.16.

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Most modern cameras allow captured images to be saved in two color spaces: (1) raw-RGB and (2) standard RGB (sRGB). The raw-RGB image represents a scene-referred sensor image whose RGB values are specific to the color sensitivities of the sensor's color filter array. The sRGB image represents a display-referred image that has been rendered through the camera's image signal processor (ISP). The rendering process involves several camera-specific photo-finishing manipulations intended to make the sRGB image visually pleasing. For applications that want to use a camera for purposes beyond photography, both the raw-RGB and sRGB color spaces are undesirable. For example, because the raw-RGB color space is dependent on the camera's sensor, it is challenging to develop applications that work across multiple cameras. Similarly, the camera-specific photo-finishing operations used to render sRGB images also hinder applications intended to run on different cameras. Interestingly, the ISP camera pipeline includes a colorimetric conversion stage where the raw-RGB images are converted to a device-independent color space. However, this image state is not accessible. In this paper, we advocate for the ability to access the colorimetric image state and recommend that cameras output a third image format that is based on this device-independent colorimetric space. To this end, we perform experiments to demonstrate that image pixel values in a colorimetric space are more similar across different makes and models than sRGB and raw-RGB.

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Ishii, Ado. "Color Space Conversion for the Laser Film Recorder Using 3-D LUT." SMPTE Motion Imaging Journal 111, no. 11 (November 2002): 525–32. http://dx.doi.org/10.5594/j16322.

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Ye, Han Kun. "A Color Error Correction Mode for Digital Camera." Applied Mechanics and Materials 44-47 (December 2010): 3706–10. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3706.

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Digital camera is the one of the main devices in the computer and multimedia technology and its color management model is the key to guarantee the color consistency in the succedent image production and transfers. The paper presents a color conversion model for digital camera based on polynomial curve generation. First, color rendering principle of digital camera is analyzed. Then digital camera data is pretreated to a unitary field to deduce final model. Third, standard color target is taken for experimental sample and substitutes color blocks in color shade district for complete color space to solve the difficulties of experimental color blocks selecting; Fourth, the model using polynomial curve generation algorithm to correct color error is deduced; Finally, the realization and experiment results show that, compared with some methods which have relatively high accuracy, the algorithm can improve color conversion accuracy and can satisfy the engineering requirement in digital camera color management

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Imamura, Masahiro, Shigeki Nakauchi, and Shiro Usui. "Extraction and Mapping of Destination Color Gamut based on Mutual Color Space Conversion by Multilayered Neural Networks." IEEJ Transactions on Electronics, Information and Systems 117, no. 1 (1997): 57–62. http://dx.doi.org/10.1541/ieejeiss1987.117.1_57.

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Mohammed, Mohammed H., Hazim G. Daway, and Jamela Jouda. "WBCs detection depending based on a binary conversion of the color component in a Ycbcr color space." IOP Conference Series: Materials Science and Engineering 928 (November 19, 2020): 072081. http://dx.doi.org/10.1088/1757-899x/928/7/072081.

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Sunakara, Rajeev, and P. Ravi Sankar. "Comparative Analysis of Color Video Enhancment Techniques." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 4 (October 10, 2013): 2484–89. http://dx.doi.org/10.24297/ijct.v11i4.3133.

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Contrast enhancement has an important role in image processing applications. This paper presents a color enhancement algorithm based on adaptive filter technique. First, the proposed method is divided into three major parts: obtain luminance image and backdrop image, adaptive modification and color restoration. different traditional color image enhancement algorithms, the adaptive filter in the algorithm takes color information into consideration. The algorithm finds the significance of color information in color image enhancement and utilizes color space conversion to obtain a much better visibility. In the practical results, the proposed method reproduces better enhancement and reduce the halo distortion compared with the bilateral methods.

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Abdel Qader, Akram. "A New Novel Hybrid Dynamic Color Segmentation Model for Road Signs in Noisy Conditions." International Journal of Software Innovation 9, no. 3 (July 2021): 1–22. http://dx.doi.org/10.4018/ijsi.2021070101.

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Image segmentation is the most important process in road sign detection and classification systems. In road sign systems, the spatial information of road signs are very important for safety issues. Road sign segmentation is a complex segmentation task because of the different road sign colors and shapes that make it difficult to use specific threshold. Most road sign segmentation studies do good in ideal situations, but many problems need to be solved when the road signs are in poor lighting and noisy conditions. This paper proposes a hybrid dynamic threshold color segmentation technique for road sign images. In a pre-processing step, the authors use the histogram analysis, noise reduction with a Gaussian filter, adaptive histogram equalization, and conversion from RGB space to YCbCr or HSV color spaces. Next, a segmentation threshold is selected dynamically and used to segment the pre-processed image. The method was tested on outdoor images under noisy conditions and was able to accurately segment road signs with different colors (red, blue, and yellow) and shapes.

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Sivabalakrishnan, M., and D. Manjula. "Fuzzy Rule-based Classification of Human Tracking and Segmentation using Color Space Conversion." International Journal of Artificial Intelligence & Applications 1, no. 4 (October 29, 2010): 70–80. http://dx.doi.org/10.5121/ijaia.2010.1406.

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Yang Jinkai, 杨金锴, 李鹏飞 Li Pengfei, 苏泽斌 Su Zebin, and 景军锋 Jing Junfeng. "Color Space Conversion Method of Digital Printing Based on Improved Extreme Learning Machine." Laser & Optoelectronics Progress 58, no. 5 (2021): 0533001–533001340. http://dx.doi.org/10.3788/lop202158.0533001.

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