DIFFERENTIAL CONTRAST BASED ADAPTIVE QUANTIZATION FOR PERCEPTUAL QUALITY OPTIMIZATION IN IMAGE CODING

被引：1

作者：

Han, Jingning ^{[1
]}

Chen, Cheng ^{[1
]}

Galligan, Frank ^{[1
]}

Massimino, Pascal ^{[1
]}

Wilkins, Paul ^{[1
]}

Chang, Wan-Teh ^{[1
]}

Guyon, Yannis ^{[1
]}

Xu, Yaowu ^{[1
]}

Bankoski, James ^{[1
]}

机构：

[1] Google LLC, Mountain View, CA 94043 USA

来源：

2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP | 2022年

关键词：

Image coding; perceptual quality;

D O I：

10.1109/ICIP46576.2022.9897648

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We consider the perceptual quality optimization in image coding through adaptive quantization. A differential contrast model is proposed to measure the visual sensitivity to the quantization distortions, and thereby deriving the spatially adaptive quantization strategy. A complementary quantitative approach is provided as a means to efficiently calculate the proposed differential contrast model. The resulting visual quality improvement is experimentally demonstrated.

引用

页码：3026 / 3030

页数：5

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