Image Quality Assessment of Computer-generated Images Based on Machine Learning and Soft Computing /

• Main Authors: Bigand, André (Author, http://id.loc.gov/vocabulary/relators/aut), Dehos, Julien (http://id.loc.gov/vocabulary/relators/aut), Renaud, Christophe (http://id.loc.gov/vocabulary/relators/aut), Constantin, Joseph (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: SpringerBriefs in Computer Science,
• Subjects: Optical data processing.; Computational intelligence.; Computer Imaging, Vision, Pattern Recognition and Graphics.; Computational Intelligence.

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...

Table of Contents:

• Introduction
• Monte-Carlo Methods for Image Synthesis
• Visual Impact of Rendering on Image Quality
• Full-reference Methods and Machine Learning
• No-reference Methods and Fuzzy Sets
• Reduced-reference Methods
• Conclusion.