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.
"synopsis" may belong to another edition of this title.
The main objective of this book is to present an introduction to vision models and their use in image and video processing applications. The book takes on an engineering and signal processing approach. It is intended for an engineering audience that wants to use and become familiar with vision models. To achieve this goal, we have chosen to organize the book around the traditional main components of vision models. Each chapter presents applications related to the aspects it models. A unique discussion on applications (digital camera, video test and measurement) is offered, as well as a report on the progress of some standard bodies. We present novel views on subjective experiments that permit engineers to understand and design such experiments in order to validate metrics and optimize image processing algorithms."Vision Models and Applications to Image and Video Processing" describes the appropriate methods to conduct subjective experiments and presents many examples. We have gathered some of the world's most prominent names to author the individual chapters. These names will be immediately recognizable to anyone working in video/image processing and/or vision science.
"About this title" may belong to another edition of this title.
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