Improved Sparse 3D Transform-Domain Collaborative Filter for Screen Content Image Denoising

被引：6

作者：

Liu, Zhi ^{[1
]}

Wang, Shuai ^{[1
]}

Zhang, Mengmeng ^{[1
]}

机构：

[1] North China Univ Technol, Beijing 100144, Peoples R China

来源：

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | 2018年 / 32卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Screen content video; block-matching; collaborative filtering; denoising; HEVC;

D O I：

10.1142/S021800141854006X

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Screen content videos or images are widely used in applications such as screen sharing. Compressed screen content videos or images may have distortions or noises because of the quantization process. This paper proposes an improved sparse 3D transform-domain collaborative filter to enhance screen content image quality by block classification and block segmentation. Experimental results show that the proposed algorithm achieves a peak signal-to-noise ratio increase and subjective visual quality improvements for reconstructed screen content images.

引用

页数：15

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