Overview
- Editors:
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Christian J. Branden Lambrecht
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EMC Media Solutions Group, Hopkinton, USA
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Table of contents (10 chapters)
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- Lisa J. Croner, Thomas Wachtler
Pages 1-19
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- Amnon Silverstein, Thom Carney, Stanley A. Klein
Pages 53-68
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- Jean-Bernard Martens, Martin Boschman
Pages 69-97
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- Karl-Heinz Bäuml, Xuemei Zhang, Brian Wandell
Pages 99-122
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- Philippe Longère, David H. Brainard
Pages 123-150
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- Jean-Bernard Martens, Lydia Meesters
Pages 151-177
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- Stefan Winkler, Murat Kunt, Christian J. van den Branden Lambrecht
Pages 201-229
About this book
I came to vision science trying to solve an engineering problem: I was trying to come up with test and measurement methodologies for digital video systems. One of the metrics I wanted to use was some measurement of image quality. After some experiments and after an overview of the literature, I had to realize that simple computational metrics, such as the mean square error, are not very effective for this purpose. This led me to study notions of vision science and vision modeling. As an engineer, I found it fascinating. Vision science uses computational tools and modeling techniques that are very similar to what we use in signal processing, yet it brings you to a new domain that lies at the intersection of engineering, biology and cognitive psychology. Over the years, vision science has made tremendous contributions to engineering and to the field of image processing in particular. Such contributions include half toning matrices for the printing industry, color correction for digital cameras, quantization matrices for image coding. As imaging devices are becoming commodities, the impact of vision science is becoming even more significant. This book is meant to appeal to an engineering audience. It is an introduction to vision science and to the design and application of vision models in engineering. To achieve this goal, we have chosen to organize the book around the main components of vision models.
