Super-Resolution Reconstruction Algorithm Based on Local Self-Similarity

被引：0

作者：

Shi Min ^{[1
]}

Yi Qingming ^{[1
]}

Zhao Xinzhong ^{[2
]}

Bai Yang ^{[1
]}

机构：

[1] Jinan Univ, Coll Informat Sci & Technol, Guangzhou 510632, Guangdong, Peoples R China

[2] Act Zhuhai Technol Co Ltd, Zhuhai 519085, Peoples R China

来源：

EIGHTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2016) | 2016年 / 10033卷

关键词：

Super-Resolution; capturing model; Self-similarity; IMAGE INTERPOLATION;

D O I：

10.1117/12.2244842

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Super-resolution has been extensively studied for decades, but its application to a real-world image still remains challenging. In this paper, a novel approach for image super-resolution algorithm based on local self-similarity (SRLS) is proposed. First, a limited window is used to bind several similar patches of the input image into a same group. Then the high-resolution image can be inferred by using the image capturing model. The experiment shows that the proposed algorithm achieves improvement in image quality and provides more details.

引用

页数：5

共 16 条

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