TY  - BOOK
AU  - Ding,Yong
ED  - SpringerLink (Online service)
TI  - Visual Quality Assessment for Natural and Medical Image
SN  - 9783662564974
AV  - TK5102.9 
U1  - 621.382 23
PY  - 2018///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Signal processing
KW  - Image processing
KW  - Speech processing systems
KW  - Optical data processing
KW  - Computers
KW  - Applied mathematics
KW  - Engineering mathematics
KW  - Signal, Image and Speech Processing
KW  - Image Processing and Computer Vision
KW  - Information Systems and Communication Service
KW  - Mathematical and Computational Engineering
N1  - Acceso multiusuario; Introduction -- Subjective Image Quality Assessment -- Human Visual System and Vision Modeling -- General Framework of Image Quality Assessment -- Image Quality Assessment Based on Human Visual System Properties -- Image Quality Assessment Based on Natural Scene Statistics -- Stereoscopic Image Quality Assessment -- Medical Image Quality Assessment -- Challenge Issues and Future Work
N2  - Image quality assessment (IQA) is an essential technique in the design of modern, large-scale image and video processing systems. This book introduces and discusses in detail topics related to IQA, including the basic principles of subjective and objective experiments, biological evidence for image quality perception, and recent research developments. In line with recent trends in imaging techniques and to explain the application-specific utilization, it particularly focuses on IQA for stereoscopic (3D) images and medical images, rather than on planar (2D) natural images. In addition, a wealth of vivid, specific figures and formulas help readers deepen their understanding of fundamental and new applications for image quality assessment technology. This book is suitable for researchers, clinicians and engineers as well as students working in related disciplines, including imaging, displaying, image processing, and storage and transmission. By reviewing and presenting the latest advances, and new trends and challenges in the field, it benefits researchers and industrial R&D engineers seeking to implement image quality assessment systems for specific applications or design/optimize image/video processing algorithms
UR  - http://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-662-56497-4
ER  -