Image recoloring for color vision deficiency compensation: a survey

People with color vision deficiency (CVD) have a reduced capability to discriminate different colors. This impairment can cause inconveniences in the individuals’ daily lives and may even expose them to dangerous situations, such as failing to read traffic signals. CVD affects approximately 200 million people worldwide. In order to compensate for CVD, a significant number of image recoloring studies have been proposed. In this survey, we briefly review the representative existing recoloring methods and categorize them according to their methodological characteristics. Concurrently, we summarize the evaluation metrics, both subjective and quantitative, introduced in the existing studies and compare the state-of-the-art studies using the experimental evaluation results with the quantitative metrics.

[1]  Xiandou Zhang,et al.  A content-dependent Daltonization algorithm for colour vision deficiencies based on lightness and chroma information , 2020, IET Image Process..

[2]  Mohd Fikree Hassan,et al.  Flexible color contrast enhancement method for red-green deficiency , 2019, Multidimensional Systems and Signal Processing.

[3]  Tien-Tsin Wong,et al.  Seamless visual sharing with color vision deficiencies , 2016, ACM Trans. Graph..

[4]  Kentaro Go,et al.  Fast contrast and naturalness preserving image recolouring for dichromats , 2021, Comput. Graph..

[5]  David R. Flatla,et al.  SPRWeb: preserving subjective responses to website colour schemes through automatic recolouring , 2013, CHI.

[6]  Hujun Bao,et al.  An Efficient Direct Volume Rendering Approach for Dichromats , 2011, IEEE Transactions on Visualization and Computer Graphics.

[7]  David R. Flatla,et al.  SSMRecolor: improving recoloring tools with situation-specific models of color differentiation , 2012, CHI.

[8]  Miklós Hoffmann,et al.  A Content-Dependent Naturalness-Preserving Daltonization Method for Dichromatic and Anomalous Trichromatic Color Vision Deficiencies , 2015 .

[9]  Holger Regenbrecht,et al.  ChromaGlasses: Computational Glasses for Compensating Colour Blindness , 2018, CHI.

[10]  Xiaodong Gu,et al.  A Fixed Transformation of Color Images for Dichromats Based on Similarity Matrices , 2007, ICIC.

[11]  Kentaro Go,et al.  Naturalness- and information-preserving image recoloring for red-green dichromats , 2019, Signal Process. Image Commun..

[12]  Ken Wakita,et al.  SmartColor: disambiguation framework for the colorblind , 2005, Assets '05.

[13]  Eberhart Zrenner,et al.  Is colour vision possible with only rods and blue-sensitive cones? , 1991, Nature.

[14]  Meng Wang,et al.  Accessible image search for colorblindness , 2010, TIST.

[15]  Abel J. P. Gomes,et al.  Recoloring Algorithms for Colorblind People , 2019, ACM Comput. Surv..

[16]  Richard Harvey,et al.  Accommodating color blind computer users , 2006, Assets '06.

[17]  Xiaoli Zhang,et al.  Contrast preserving image decolorization combining global features and local semantic features , 2018, The Visual Computer.

[18]  C. H. Graham,et al.  STUDIES OF COLOR BLINDNESS: A UNILATERALLY DICHROMATIC SUBJECT , 1959 .

[19]  Robert Geist,et al.  Smart Depiction for Visual Communication Detail Preserving Reproduction of Color Images for , 2022 .

[20]  Manuel Menezes de Oliveira Neto,et al.  A Physiologically-based Model for Simulation of Color Vision Deficiency , 2009, IEEE Transactions on Visualization and Computer Graphics.

[21]  Bruce Gooch,et al.  Color2Gray: salience-preserving color removal , 2005, SIGGRAPH 2005.

[22]  Raveendran Paramesran,et al.  Naturalness preserving image recoloring method for people with red-green deficiency , 2017, Signal Process. Image Commun..

[23]  Ryan S. Renslow,et al.  Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data , 2017, PloS one.

[24]  Wellington Pinheiro dos Santos,et al.  An adaptive fuzzy-based system to simulate, quantify and compensate color blindness , 2017, Integr. Comput. Aided Eng..

[25]  D. B. Judd Fundamental studies of color vision from 1860 to 1960. , 1966, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Mohammed Bennamoun,et al.  Color vision deficiency datasets & recoloring evaluation using GANs , 2020, Multimedia Tools and Applications.

[27]  Maria Petrou,et al.  Optimising the Choice of Colours of an Image Database for Dichromats , 2005, MLDM.

[28]  Robert Geist,et al.  Re‐coloring Images for Gamuts of Lower Dimension , 2005, Comput. Graph. Forum.

[29]  Manuel Menezes de Oliveira Neto,et al.  An improved contrast enhancing approach for color-to-grayscale mappings , 2008, The Visual Computer.

[30]  Françoise Viénot,et al.  Digital video colourmaps for checking the legibility of displays by dichromats , 1999 .

[31]  J. Nathans,et al.  Opsin genes, cone photopigments, color vision, and color blindness , 1999 .

[32]  Tai-Shan Liao,et al.  Hardware Digital Color Enhancement for Color Vision Deficiencies , 2011 .

[33]  Sheng-Jyh Wang,et al.  Information Preserving Color Transformation for Protanopia and Deuteranopia , 2007, IEEE Signal Processing Letters.

[34]  Kentaro Go,et al.  ALCC-Glasses: Arriving Light Chroma Controllable Optical See-Through Head-Mounted Display System for Color Vision Deficiency Compensation , 2020, Applied Sciences.

[35]  Manuel Menezes de Oliveira Neto,et al.  Eurographics/ Ieee-vgtc Symposium on Visualization 2010 Real-time Temporal-coherent Color Contrast Enhancement for Dichromats , 2022 .

[36]  Edward K. Wong,et al.  Quantification and Standardized Description of Color Vision Deficiency Caused by Anomalous Trichromats—Part I: Simulation and Measurement , 2008, EURASIP J. Image Video Process..

[37]  Richard Harvey,et al.  An interface to support color blind computer users , 2007, CHI.

[38]  Chun-Rong Huang,et al.  Key Color Priority Based Image Recoloring for Dichromats , 2010, PCM.

[39]  David Zhang,et al.  FSIM: A Feature Similarity Index for Image Quality Assessment , 2011, IEEE Transactions on Image Processing.

[40]  Kentaro Go,et al.  Processing images for red–green dichromats compensation via naturalness and information-preservation considered recoloring , 2019, The Visual Computer.

[41]  Vittorio Scarano,et al.  Efficient edge-services for colorblind users , 2006, WWW '06.

[42]  D B JUDD,et al.  The color perceptions of deuteranopic and protanopic observers. , 1948, Journal of the Optical Society of America.

[43]  Binjie Qin,et al.  WpmDecolor: weighted projection maximum solver for contrast-preserving decolorization , 2019, The Visual Computer.

[44]  Meng Wang,et al.  Accessible image search , 2009, MM '09.

[45]  Manuel Menezes de Oliveira Neto,et al.  An Efficient Naturalness-Preserving Image-Recoloring Method for Dichromats , 2008, IEEE Transactions on Visualization and Computer Graphics.

[46]  Shigeki Nakauchi,et al.  Detection and modification of confusing color combinations for red‐green dichromats to achieve a color universal design , 2008 .

[47]  Manabu Ichikawa,et al.  Web-Page Color Modification for Barrier-Free Color Vision with Genetic Algorithm , 2003, GECCO.

[48]  Reiner Lenz,et al.  Riemann Geometric Color-Weak Compensation for Individual Observers , 2014, HCI.

[49]  Ye Seul Baek,et al.  Flexible Technique to Enhance Color-image Quality for Color-deficient Observers , 2018 .

[50]  J D Mollon,et al.  Computerized simulation of color appearance for dichromats. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

[51]  Xiaodong Gu,et al.  Color discrimination enhancement for dichromats using self-organizing color transformation , 2009, Inf. Sci..

[52]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.