{"product_id":"color-constancy-hardback-9780470058299","title":"Color Constancy (Hardback) 9780470058299","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eColor Constancy\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eMarc Ebner (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470058299, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 20 April 2007\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e408 pages\u003cbr\u003e25.2 x 17.5 x 2.5 cm, 1.007 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\"I think Ebner's \u003ci\u003eColor Constancy\u003c\/i\u003e is an excellent summary of current algorithms, and provides empirical tests in a womanlike manner … As an inclusive time capsule, it has no parallel, and therefore is a valuable contribution to the field.\" (\u003ci\u003eColor Research and Application\u003c\/i\u003e, June 2008)\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eA human observer is able to recognize the color of objects irrespective of the light used to illuminate them. This is called color constancy. A digital camera uses a sensor to measure the reflected light, meaning that the measured color at each pixel varies according to the color of the illuminant. Therefore, the resulting colors may not be the same as the colors that were perceived by the observer. Obtaining color constant descriptors from image pixels is not only important for digital photography, but also valuable for computer vision, color-based automatic object recognition, and color image processing in general.  \u003cp\u003eThis book provides a comprehensive introduction to the field of color constancy, describing all the major color constancy algorithms, as well as presenting cutting edge research in the area of color image processing. Beginning with an in-depth look at the human visual system, Ebner goes on to:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eexamine the theory of color image formation, color reproduction and different color spaces;\u003c\/li\u003e \u003cli\u003ediscuss algorithms for color constancy under both uniform and non-uniform illuminants;\u003c\/li\u003e \u003cli\u003edescribe methods for shadow removal and shadow attenuation in digital images;\u003c\/li\u003e \u003cli\u003eevaluate the various algorithms for object recognition and color constancy and compare this to data obtained from experimental psychology;\u003c\/li\u003e \u003cli\u003eset out the different algorithms as pseudo code in an appendix at the end of the book.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eColor Constancy\u003c\/i\u003e is an ideal reference for practising engineers, computer scientists and researchers working in the area of digital color image processing. It may also be useful for biologists or scientists in general who are interested in computational theories of the visual brain and bio-inspired engineering systems.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eSeries Preface xi\u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 What is Color Constancy? 1\u003c\/p\u003e \u003cp\u003e1.2 Classic Experiments 3\u003c\/p\u003e \u003cp\u003e1.3 Overview 7\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 The Visual System 9\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Eye and Retina 9\u003c\/p\u003e \u003cp\u003e2.2 Visual Cortex 16\u003c\/p\u003e \u003cp\u003e2.3 On the Function of the Color Opponent Cells 30\u003c\/p\u003e \u003cp\u003e2.4 Lightness 31\u003c\/p\u003e \u003cp\u003e2.5 Color Perception Correlates with Integrated Reflectances 32\u003c\/p\u003e \u003cp\u003e2.6 Involvement of the Visual Cortex in Color Constancy 35\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Theory of Color Image Formation 39\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Analog Photography 41\u003c\/p\u003e \u003cp\u003e3.2 Digital Photography 46\u003c\/p\u003e \u003cp\u003e3.3 Theory of Radiometry 47\u003c\/p\u003e \u003cp\u003e3.4 Reflectance Models 52\u003c\/p\u003e \u003cp\u003e3.5 Illuminants 56\u003c\/p\u003e \u003cp\u003e3.6 Sensor Response 60\u003c\/p\u003e \u003cp\u003e3.7 Finite Set of Basis Functions 63\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Color Reproduction 67\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Additive and Subtractive Color Generation 68\u003c\/p\u003e \u003cp\u003e4.2 Color Gamut 69\u003c\/p\u003e \u003cp\u003e4.3 Computing Primary Intensities 69\u003c\/p\u003e \u003cp\u003e4.4 CIE XYZ Color Space 70\u003c\/p\u003e \u003cp\u003e4.5 Gamma Correction 79\u003c\/p\u003e \u003cp\u003e4.6 Von Kries Coefficients and Sensor Sharpening 83\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Color Spaces 87\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 RGB Color Space 87\u003c\/p\u003e \u003cp\u003e5.2 sRGB 87\u003c\/p\u003e \u003cp\u003e5.3 CIE \u003ci\u003eL\u003c\/i\u003e∗\u003ci\u003eu\u003c\/i\u003e∗\u003ci\u003ev\u003c\/i\u003e∗Color Space 89\u003c\/p\u003e \u003cp\u003e5.4 CIE \u003ci\u003eL\u003c\/i\u003e∗\u003ci\u003ea\u003c\/i\u003e∗\u003ci\u003eb\u003c\/i\u003e∗Color Space 92\u003c\/p\u003e \u003cp\u003e5.5 CMY Color Space 93\u003c\/p\u003e \u003cp\u003e5.6 HSI Color Space 93\u003c\/p\u003e \u003cp\u003e5.7 HSV Color Space 96\u003c\/p\u003e \u003cp\u003e5.8 Analog and Digital Video Color Spaces 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Algorithms for Color Constancy under Uniform Illumination 103\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 White Patch Retinex 104\u003c\/p\u003e \u003cp\u003e6.2 The Gray World Assumption 106\u003c\/p\u003e \u003cp\u003e6.3 Variant of Horn’s Algorithm 113\u003c\/p\u003e \u003cp\u003e6.4 Gamut-constraint Methods 115\u003c\/p\u003e \u003cp\u003e6.5 Color in Perspective 121\u003c\/p\u003e \u003cp\u003e6.6 Color Cluster Rotation 128\u003c\/p\u003e \u003cp\u003e6.7 Comprehensive Color Normalization 129\u003c\/p\u003e \u003cp\u003e6.8 Color Constancy Using a Dichromatic Reflection Model 134\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Algorithms for Color Constancy under Nonuniform Illumination 143\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 The Retinex Theory of Color Vision 143\u003c\/p\u003e \u003cp\u003e7.2 Computation of Lightness and Color 154\u003c\/p\u003e \u003cp\u003e7.3 Hardware Implementation of Land’s Retinex Theory 166\u003c\/p\u003e \u003cp\u003e7.4 Color Correction on Multiple Scales 169\u003c\/p\u003e \u003cp\u003e7.5 Homomorphic Filtering 170\u003c\/p\u003e \u003cp\u003e7.6 Intrinsic Images 175\u003c\/p\u003e \u003cp\u003e7.7 Reflectance Images from Image Sequences 188\u003c\/p\u003e \u003cp\u003e7.8 Additional Algorithms 190\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Learning Color Constancy 193\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Learning a Linear Filter 193\u003c\/p\u003e \u003cp\u003e8.2 Learning Color Constancy Using Neural Networks 194\u003c\/p\u003e \u003cp\u003e8.3 Evolving Color Constancy 198\u003c\/p\u003e \u003cp\u003e8.4 Analysis of Chromatic Signals 204\u003c\/p\u003e \u003cp\u003e8.5 Neural Architecture based on Double Opponent Cells 205\u003c\/p\u003e \u003cp\u003e8.6 Neural Architecture Using Energy Minimization 209\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Shadow Removal and Brightening 213\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Shadow Removal Using Intrinsic Images 213\u003c\/p\u003e \u003cp\u003e9.2 Shadow Brightening 215\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Estimating the Illuminant Locally 219\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Local Space Average Color 219\u003c\/p\u003e \u003cp\u003e10.2 Computing Local Space Average Color on a Grid of Processing Elements 221\u003c\/p\u003e \u003cp\u003e10.3 Implementation Using a Resistive Grid 230\u003c\/p\u003e \u003cp\u003e10.4 Experimental Results 237\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Using Local Space Average Color for Color Constancy 239\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Scaling Input Values 239\u003c\/p\u003e \u003cp\u003e11.2 Color Shifts 241\u003c\/p\u003e \u003cp\u003e11.3 Normalized Color Shifts 246\u003c\/p\u003e \u003cp\u003e11.4 Adjusting Saturation 249\u003c\/p\u003e \u003cp\u003e11.5 Combining White Patch Retinex and the Gray World Assumption 251\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Computing Anisotropic Local Space Average Color 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Nonlinear Change of the Illuminant 255\u003c\/p\u003e \u003cp\u003e12.2 The Line of Constant Illumination 257\u003c\/p\u003e \u003cp\u003e12.3 Interpolation Methods 259\u003c\/p\u003e \u003cp\u003e12.4 Evaluation of Interpolation Methods 262\u003c\/p\u003e \u003cp\u003e12.5 Curved Line of Constant Illumination 265\u003c\/p\u003e \u003cp\u003e12.6 Experimental Results 267\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Evaluation of Algorithms 275\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Histogram-based Object Recognition 275\u003c\/p\u003e \u003cp\u003e13.2 Object Recognition under Changing Illumination 279\u003c\/p\u003e \u003cp\u003e13.3 Evaluation on Object Recognition Tasks 282\u003c\/p\u003e \u003cp\u003e13.4 Computation of Color Constant Descriptors 290\u003c\/p\u003e \u003cp\u003e13.5 Comparison to Ground Truth Data 299\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Agreement with Data from Experimental Psychology 303\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Perceived Color of Gray Samples When Viewed under Colored Light 303\u003c\/p\u003e \u003cp\u003e14.2 Theoretical Analysis of Color Constancy Algorithms 305\u003c\/p\u003e \u003cp\u003e14.3 Theoretical Analysis of Algorithms Based on Local Space Average Color 312\u003c\/p\u003e \u003cp\u003e14.4 Performance of Algorithms on Simulated Stimuli 316\u003c\/p\u003e \u003cp\u003e14.5 Detailed Analysis of Color Shifts 319\u003c\/p\u003e \u003cp\u003e14.6 Theoretical Models for Color Conversion 320\u003c\/p\u003e \u003cp\u003e14.7 Human Color Constancy 324\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Conclusion 327\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAppendix A Dirac Delta Function 329\u003c\/p\u003e \u003cp\u003eAppendix B Units of Radiometry and Photometry 331\u003c\/p\u003e \u003cp\u003eAppendix C Sample Output from Algorithms 333\u003c\/p\u003e \u003cp\u003eAppendix D Image Sets 339\u003c\/p\u003e \u003cp\u003eAppendix E Program Code 349\u003c\/p\u003e \u003cp\u003eAppendix F Parameter Settings 363\u003c\/p\u003e \u003cp\u003eBibliography 369\u003c\/p\u003e \u003cp\u003eList of Symbols 381\u003c\/p\u003e \u003cp\u003eIndex 385\u003c\/p\u003e \u003cp\u003ePermissions 391\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Electronics \u0026amp; communications engineering [\u003ca title=\"See our other books on Electronics \u0026amp; communications engineering\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Electronics%20\u0026amp;%20communications%20engineering%20%5BTJ%5D%22\"\u003eTJ\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52256844546328,"sku":"9780470058299","price":103.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780470058299.jpg?v=1781275212","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/color-constancy-hardback-9780470058299","provider":"Freshly Printed Books","version":"1.0","type":"link"}