Vision Models and Applications to Image and Video Processing

1. Front Matter

   Pages i-x

   PDF

2. Introduction to Neurophysiology of the Primate Visual System

   • Lisa J. Croner, Thomas Wachtler

   Pages 1-19

3. Modeling Brightness Perception

   • Hans du Buf

   Pages 21-36

4. Pattern Masking

   • Geoffrey M. Boynton

   Pages 37-52

5. Modeling Contrast Thresholds

   • Amnon Silverstein, Thom Carney, Stanley A. Klein

   Pages 53-68

6. The Psychophysical Measurement of Image Quality

   • Jean-Bernard Martens, Martin Boschman

   Pages 69-97

7. Color Spaces and Color Metrics

   • Karl-Heinz Bäuml, Xuemei Zhang, Brian Wandell

   Pages 99-122

8. Simulation of Digital Camera Images from Hyperspectral Input

   • Philippe Longère, David H. Brainard

   Pages 123-150

9. Single-Ended Instrumental Measurement of Image Quality

   • Jean-Bernard Martens, Lydia Meesters

   Pages 151-177

10. Engineering Observations from Spatiovelocity and Spatiotemporal Visual Models

    • Scott Daly

    Pages 179-200

11. Vision and Video: Models and Applications

    • Stefan Winkler, Murat Kunt, Christian J. van den Branden Lambrecht

    Pages 201-229

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.

• Color space
• Perception
• Signal
• Standard
• algorithms
• image processing
• metrics
• modeling
• signal processing
• simulation

• EMC Media Solutions Group, Hopkinton, USA

  Christian J. Branden Lambrecht

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