Visually Lossless Perceptual Image Coding Based on Natural- Scene Masking Models ( Recent Advances in Image and Video Coding )

Publication series : Recent Advances in Image and Video Coding

Author: Yi Zhang Md Mushfiqul Alam and Damon M. Chandler  

Publisher: IntechOpen‎

Publication year: 2016

E-ISBN: INT6260265362

P-ISBN(Paperback): 9789535127758

P-ISBN(Hardback):  9789535127765

Subject: TP317.4 Image processing software;TP39 computer application

Keyword: 计算机的应用,图像处理软件

Language: ENG

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Visually Lossless Perceptual Image Coding Based on Natural- Scene Masking Models

Description

Perceptual coding is a subdiscipline of image and video coding that uses models of human visual perception to achieve improved compression efficiency. Nearly, all image and video coders have included some perceptual coding strategies, most notably visual masking. Today, modern coders capitalize on various basic forms of masking such as the fact that distortion is harder to see in very dark and very bright regions, in regions with higher frequency content, and in temporal regions with abrupt changes. However, beyond these obvious forms of masking, there are many other masking phenomena that occur (and co-occur) when viewing natural imagery. In this chapter, we present our latest research in perceptual image coding using natural-scene masking models. We specifically discuss: (1) how to predict local distortion visibility using improved natural-scene masking models and (2) how to apply the models to high efficiency video coding (HEVC). As we will demonstrate, these techniques can offer 10–20% fewer bits than baseline HEVC in the ultra-high-quality regime.

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