Visual Quality Assessment by Machine Learning

The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also...

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Main Authors: Xu, Long, Lin, Weisi (Author), Kuo, C.-C. Jay (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Singapore Springer Singapore 2015, 2015
Edition:1st ed. 2015
Series:SpringerBriefs in Signal Processing
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Summary:The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also encompasses the preliminary knowledge of Machine Learning (ML) to VQA tasks and newly developed ML techniques for the purpose. Hence, firstly, it is particularly helpful to the beginner-readers (including research students) to enter into VQA field in general and LB-VQA one in particular. Secondly, new development in VQA and LB-VQA particularly are detailed in this book, which will give peer researchers and engineers new insights in VQA.
Physical Description:XIV, 132 p. 19 illus., 16 illus. in color online resource
ISBN:9789812874689