Visual Quality Assessment for Natural and Medical Image

• Κύριος συγγραφέας: Ding, Yong (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Θέματα: Signal processing.; Image processing.; Speech processing systems.; Optical data processing.; Computers.; Applied mathematics.; Engineering mathematics.; Signal, Image and Speech Processing.; Image Processing and Computer Vision.; Information Systems and Communication Service.; Mathematical and Computational Engineering.

 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. 

 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.