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Relevant bibliographies by topics / Color space conversion

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Academic literature on the topic 'Color space conversion'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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Journal articles on the topic "Color space conversion"

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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Color space conversion"

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Patil, Sreenivas. "Reconfigurable hardware for color space conversion /." Online version of thesis, 2008. http://hdl.handle.net/1850/7756.

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BIANCO, SIMONE. "Color correction algorithms for digital cameras." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2010. http://hdl.handle.net/10281/7819.

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The image recorded by a digital camera mainly depends on three factors: the physical content of the scene, the illumination incident on the scene, and the characteristics of the camera. This leads to a problem for many applications where the main interest is in the color rendition accuracy of the scene acquired. It is known that the color reproduction accuracy of a digital imaging acquisition device is a key factor to the overall perceived image quality, and that there are mainly two modules responsible for it: the former is the illuminant estimation and correction module, the latter is the color matrix transformation. These two modules together form what may be called the color correction pipeline. This thesis has the objective to design and test new and more robust modules for the color correction pipeline, studying and exploiting the existing crosstalks in order to obtain a higher color reproduction accuracy. The first module considered is the illuminant estimation and correction one; many illuminant estimation solutions have been proposed in the last few years, although it is known that the problem addressed is actually ill-posed as its solution lack uniqueness or stability. To cope with this problem, different solutions usually exploit some assumptions about the statistical properties of the expected illuminants and/or of the object reflectances in the scene. In the last few years two research areas that are important in the context of improving the performance of color constancy algorithms have been highlighted: making additional measurements at the time of image capture (i.e. using more color pixel information), and algorithm combining (i.e. using two or more estimations of the illuminants). In this thesis a third hypothesis is investigated: the use of low level visual information to improve illuminant estimation. The second module considered is the transformation of the camera-dependent RGB image data into a standard RGB color space. This transformation, usually called color correction matrix or color matrixing, is needed because the spectral sensitivity functions of the sensor color channels rarely match those of the desired output color space (usually sRGB). The color correction matrix transformation is usually optimized assuming that the illuminant in the scene has been successfully estimated and compensated for. Both the illuminant estimation process and the color correction matrix concur in the formation of the overall perceived image quality. The two processes have always been studied separately, thus ignoring the interactions between them. In this thesis the interactions between the illuminant estimation process and the color correction matrix in the formation of the overall color accuracy are investigated, especially when the white point estimation is imperfect. How the color correction transform amplifies the illuminant estimation errors is also investigated. Furthermore, it is shown that it is possible to incorporate knowledge about the illuminant estimation behavior in the optimization of the color correction matrix to alleviate the error amplification. It is demonstrated that a fixed device chromatic response characterization, which is often adopted, is not able to produce good color accuracy in most situations. New strategies to improve color accuracy under both perfect and imperfect white point estimation are proposed, which clearly suggest that adaptive color transformations have to be preferred in order to improve the color accuracy.

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Rodrigues, Carlos André Mendonça. "Color space conversion in hardware for multimedia applications." Master's thesis, 2015. https://repositorio-aberto.up.pt/handle/10216/88222.

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Rodrigues, Carlos André Mendonça. "Color space conversion in hardware for multimedia applications." Dissertação, 2015. https://repositorio-aberto.up.pt/handle/10216/88222.

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Wang, Chien-Chung, and 王建中. "The Hardware Architecture Design for Cube-root and Color Space Conversion." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/93908490441359952745.

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碩士
國立雲林科技大學
電子與資訊工程研究所碩士班
90
Various color spaces have been reported in an attempt to identify a uniform perceptual color space for color measurement and prediction purposes. CIE (Commission Internationale de l''Eclairage) recommends one linear transformation to get the XYZ color space, and then, one non-linear transformation is used to get the L*a*b* color space. The design and implementation of hardware architecture, which can perform real time conversion from the RGB color coordinates to standard CIE L*a*b* color coordinates, is studied in this thesis. To calculate the cube-root in non-linear transformation, we propose the approximate arithmetic algorithms and the corresponding hardware architecture to replace the look-up tables. The accuracy of the color coordinate transform is simulated under Matlab programming tool. Then using the Verilog HDL programming language and SYNOPSYS synthesis tool to estimate and forecast its hardware performance. Finally, the implemented architecture for cube-root is faster than the LUT, and the presented combinational logic is less than the most recent published works for color space conversion.

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Lin, Zheng-Hui, and 林政輝. "GPU-Acceleration of High Performance CIE-Lab Color Space Conversion for Fully Polarimetric Synthetic Aperture Radar Images." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/4b52y9.

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碩士
國立臺北科技大學
電機工程系所
105
Color encoding or assignment of multi-polarization or fully polarimetric synthetic aperture radar (PolSAR) image is vital for visual display and interpretation of the polarimetric information. It is a common practice to use RGB or HIS color space to display the chromatic information for polarization-encoded model-based target　decomposition of PolSAR images. However, to express the multi partial Pol SAR’s chroma, the basic RGB area is not cover all the perception system of human. Our research used the frame of color distribution which based on the evenly CIE-Lab color space, for better visual aware and information explanation. Let color have strongly visual explanation which through every kinds of parameter. The new color distribution not only keep the pole feature’s color but also enhance the total power of target’s information. But it spends much time to converse the color space from PolSAR image. Thus, we adopt the Compute Unified Device Architecture (CUDA) which is parallel structure of Graphics Processing Units (GPU) to speed up the transferring-time. The experimental result shows that we do the data’s conversion with parallel structure not only can be more efficient on the running time than using CPU but get the correct color space.

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JIANG, JI-HONG, and 江吉弘. "CUDA’s Implementation of High Performance CIE-Lab Color Space Conversion for Fully Polarimetric Synthetic Aperture Radar Images." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/nkycbt.

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碩士
國立臺北科技大學
電機工程系
107
Images of the Polarimetric Synthetic Aperture Radar (POLSAR) are critical for color coding or visual interpretation and polarization. The RGB color space is usually used to display color information for polar coded PolSAR images, based on the color information decomposed by the PolSAR model. However, in order to represent the chromaticity of a multi-polar PolSAR picture, the use of the RGB color space does not completely cover the human visual perception system. In order to improve the overall efficiency, based on the reference [8] CIE-Lab and RGB conversion methods, research and analysis, this paper uses Visual Profiler and clock () function analysis, found in the color distribution and The conversion between CIE-Lab and RGB is slower. The size of the PolSAR image used in this experiment is larger than that of the general SAR image size, and the calculation is relatively time consuming. This paper uses Visual Profiler for analysis and puts the data into the CUDA architecture of our design. Three chapters. Therefore, this paper uses GPU (Compute Unified Device Architecture) of GPU (Graphics Processing Units, GPU) parallel architecture to accelerate the efficiency of the whole method. The experimental results prove that the parallel architecture proposed in this paper is used to calculate the information space. The conversion has a faster execution time in the program execution time, and has a significant performance improvement compared to the CPU only, and the correct color space can be obtained.

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Books on the topic "Color space conversion"

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Scribble, 2. Book for Atmospheric and Space Scientists - Pro Series One: 150-Page Lined Work Decor for Professionals to Write in, with Individually Numbered Pages and Metric/Imperial Conversion Charts. Vibrant and Glossy Color Cover. Independently Published, 2019.

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Book chapters on the topic "Color space conversion"

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Seo, Jong Wan, and Myung Chul Shin. "Fast and Accurate Color Space Conversion Matrix." In Advanced Nondestructive Evaluation I, 1297–300. Stafa: Trans Tech Publications Ltd., 2006. http://dx.doi.org/10.4028/0-87849-412-x.1297.

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Sridhar, C. S., G. Mahadevan, S. K. Khadar Basha, and P. Sudir. "Conversion from Lossless to Gray Scale Image Using Color Space Conversion Module." In Computational Vision and Bio-Inspired Computing, 1137–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37218-7_119.

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Hanumantharaju, M. C., G. R. Vishalakshi, Srinivas Halvi, and S. B. Satish. "A Novel FPGA Based Reconfigurable Architecture for Image Color Space Conversion." In Communications in Computer and Information Science, 292–301. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29216-3_32.

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Bao, Xinyue, Wangan Song, and Sheng Liu. "Research on Color Space Conversion Model from CMYK to CIE-LAB Based on GRNN." In Image and Video Technology, 252–61. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75786-5_21.

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Yu, Weibo, Liming Zheng, Yanhui Ma, and Keping Liu. "Research on Method of Highlight Elimination Based on Color Space Conversion in Metal Images." In Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation, 471–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49370-0_50.

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Sridhar, C. S., G. Mahadevan, S. K. Khadar Basha, B. N. Shobha, and S. Pavan. "Design and Development for Image Transmission Through Low Powered Wireless Networks Using Color Space Conversion Module." In Innovative Data Communication Technologies and Application, 37–44. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38040-3_4.

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Farr, Marcus, Andrea Macruz, and Alexandre Ulson. "Material Response: Technology, Material Systems and Responsive Design." In Proceedings of the 2021 DigitalFUTURES, 211–20. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5983-6_20.

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AbstractThis paper investigates the role technology and materials play in making meaningful connections between people, architectural space and the workplace. It indicates that design can synergize with responsive technology and material systems to leverage new power for future workplace interaction design. We have created a spatial prototype paired with a series of simulations that act as a proposal to stimulate workplace interaction. The project employs a responsive ceiling that combines a fluid computational pattern with temperature-responsive bi-material laminates with thermochromic coatings and electrically programmed micro-controllers. The project is then connected to a computer code that computes readings based upon ongoing interactions with humans wearing body sensors. The methodology categorizes the simulation results into aroused states and calm states. As the computational patterns and colors change, we are made aware of the relationships between space, technology, and the human sensorium. This conversation brings insight into how we can design more effectively for workplace interactions.

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"Color Space Conversions." In Digital Video Quality, 155–56. West Sussex, England: John Wiley & Sons Ltd,, 2013. http://dx.doi.org/10.1002/9780470024065.app1.

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McKee, Kimberly D., and Denise A. Delgado. "Epilogue." In Degrees of Difference, 165–72. University of Illinois Press, 2020. http://dx.doi.org/10.5622/illinois/9780252043185.003.0010.

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Weaving together the chapters in Degrees of Difference: Reflections of Women of Color and Indigenous Women on Graduate School is a commitment to demonstrate how women of color cultivate community and a sense of self, while simultaneously resisting oppression and microaggression in order to survive and thrive in a space that was never meant for them to succeed. The Epilogue calls attention to how the contributors exist in conversation with one another, unleashing their inner feminist killjoy as they speak to the sense of alienation experienced as a result of lack of understanding faced within cohorts, departments, and families. At the same time, these women reveal the mechanisms that allowed them to find support in friends, colleagues, and mentors in order to negotiate imposter syndrome and develop a sense of belonging in the academy. The conclusion illuminates strategies that women of color employ as they resist attempts of further marginalization within the academy.

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gill, alicia sanchez. "Organizing Dilemmas across U.S.-Based Social Justice Movement Spaces." In Wicked Problems, 107–18. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780197632819.003.0008.

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This chapter examines how funding from influential donors can play a pivotal role in activism, while also introducing risks. These risks include the co-optation of the mission, the sidelining of experiential knowledge and activist voices, and the dilution of the core message. Focusing on INCITE!, a network of radical feminists of color, the chapter picks up the conversation around the gendered dilemmas of leadership in movement spaces. The chapter invites a series of essays, in the style of self-reflective narratives, which elevate the stories of leaders who live at the intersections of many marginalized identities. In the crucible of their struggles, it presents the internal conflicts faced by movement leaders with intersectional identities as they are confronted with competing needs and demands from the many marginalized groups with whom they identify.

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Conference papers on the topic "Color space conversion"

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Chase, Patrick, and Gary Vondran. "GPU color space conversion." In IS&T/SPIE Electronic Imaging, edited by John D. Owens, I.-Jong Lin, Yu-Jin Zhang, and Giordano B. Beretta. SPIE, 2011. http://dx.doi.org/10.1117/12.876678.

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Lee, Dah-Jye. "Color space conversion for linear color grading." In Intelligent Systems and Smart Manufacturing, edited by David P. Casasent. SPIE, 2000. http://dx.doi.org/10.1117/12.403782.

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Oinosho, Taichi, Minako Kameyama, and Akira Taguchi. "Color Conversion Formulae between RGB Color Space and HSI Color Space for Color Image Processing." In 2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE, 2021. http://dx.doi.org/10.1109/ispacs51563.2021.9651118.

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Xue, Juan, and Xudong Cao. "Color space conversion based on FPGA." In 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE). IEEE, 2012. http://dx.doi.org/10.1109/csae.2012.6272806.

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LeHoty, David A. "Normalization factors in color space conversion." In Electronic Imaging 2008, edited by Reiner Eschbach, Gabriel G. Marcu, and Shoji Tominaga. SPIE, 2008. http://dx.doi.org/10.1117/12.775562.

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Dai, Jingjing, Oscar C. Au, Wen Yang, Chao Pang, Feng Zou, and Xing Wen. "Color video denoising based on adaptive color space conversion." In 2010 IEEE International Symposium on Circuits and Systems - ISCAS 2010. IEEE, 2010. http://dx.doi.org/10.1109/iscas.2010.5538013.

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Kasson, James M., Wil Plouffe, and Sigfredo I. Nin. "Tetrahedral interpolation technique for color space conversion." In IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, edited by Ricardo J. Motta and Hapet A. Berberian. SPIE, 1993. http://dx.doi.org/10.1117/12.149035.

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Lv, Guangwu, and Peng Cao. "Color Space Conversion Technology and Comparative Research." In ICIT 2020: IoT and Smart City. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3446999.3447021.

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Gao, George Z. "The design of ICC color space conversion." In 2010 IEEE International Conference on Advanced Management Science (ICAMS). IEEE, 2010. http://dx.doi.org/10.1109/icams.2010.5553301.

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Takeuchi, Masaru, Shintaro Saika, Yusuke Sakamoto, Yasutaka Matsuo, and Jiro Katto. "A study on color-space conversion method considering color information restoration." In 2018 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 2018. http://dx.doi.org/10.1109/icce.2018.8326246.

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