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Image Quality Assessment of Computer-generated Images : Based on Machine Learning and Soft Computing by André Bigand; Julien Dehos; Christophe Renaud; Joseph Constantin is a nonfiction available to read on EtoBox.

What is Image Quality Assessment of Computer-generated Images : Based on Machine Learning and Soft Computing about?

1 online resource Image Quality Assessment is well-known for measuring the perceived image degradation of natural scene images but is still an emerging topic for computer-generated images. This book addresses this problem and presents recent advances based on soft computing. It is aimed at students, practitioners and researchers in the field of image processing and related areas such as computer graphics and visualization. In this book, we first clarify the differences between natural scene images and computer-generated images, and address the problem of Image Quality Assessment (IQA) by focusing on the visual perception of noise. Rather than using known perceptual models, we first investigate the use of soft computing approaches, classically used in Artificial Intelligence, as full-reference and reduced-reference metrics. Thus, by creating Learning Machines, such as SVMs and RVMs, we can assess the perceptual quality of a computer-generated image. We also investigate the use of interval-valued fuzzy sets as a no-reference metric. These approaches are treated both theoretically and practically, for the complete process of IQA. The learning step is performed using a database built f

Who reads Image Quality Assessment of Computer-generated Images : Based on Machine Learning and Soft Computing?

Author

André Bigand; Julien Dehos; Christophe Renaud; Joseph Constantin

Publisher

Springer International Publishing : Imprint: Springer

Published

2018

Language

EN

ISBN

9783319735429

Category

nonfiction

Subjects

Computer Science, Engineering, Technology