Gaussian Noised Single-Image Super Resolution Reconstruction

被引：0
|
作者：
Qin, Fengqing [1 ]
Zhu, Lihong [1 ]
Cao, Lilan [1 ]
Yang, Wanan [1 ]
机构：
[1] Yibin Univ, Inst Comp Sci & Technol, Yibin 644000, Peoples R China
来源：
FRONTIERS OF MECHANICAL ENGINEERING AND MATERIALS ENGINEERING II, PTS 1 AND 2 | 2014年 / 457-458卷
关键词：
Single-image; Super resolution; Gaussian noise; Wiener filter; Iterative back projection; SUPERRESOLUTION;
D O I：
10.4028/www.scientific.net/AMM.457-458.1032
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A framework is proposed to reconstruct a super resolution image from a single low resolution image with Gaussian noise. The degrading processes of Gaussian blur, down-sampling, and Gaussian noise are all considered. For the low resolution image, the Gaussian noise is reduced through Wiener filtering algorithm. For the de-noised low resolution image, iterative back projection algorithm is used to reconstruct a super resolution image. Experiments show that de-noising plays an important part in single-image super resolution reconstruction. In the super reconstructed image, the Gaussian noise is reduced effectively and the peak signal to noise ratio (PSNR) is increased.
引用
收藏
页码：1032 / 1036
页数：5
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