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Visual quality assessment for natura...

Ding, Yong.

Visual quality assessment for natural and medical image

Record Type:	Electronic resources : Monograph/item
Title/Author:	Visual quality assessment for natural and medical imageby Yong Ding.
Author:	Ding, Yong.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg :2018.
Description:	x, 272 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Engineering.
Online resource:	http://dx.doi.org/10.1007/978-3-662-56497-4
ISBN:	9783662564974$q(electronic bk.)

Visual quality assessment for natural and medical image
Ding, Yong.

Visual quality assessment for natural and medical image[electronic resource] /by Yong Ding. - Berlin, Heidelberg :Springer Berlin Heidelberg :2018. - x, 272 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783662564974$q(electronic bk.)

Standard No.: 10.1007/978-3-662-56497-4doiSubjects--Topical Terms:

210888
Engineering.

LC Class. No.: TK7882.S65 / D564 2018

Dewey Class. No.: 621.367

Visual quality assessment for natural and medical image
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505 0 $a 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.
520 $a 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.
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