Super-resolution reconstruction of images based on uncontrollable microscanning and genetic algorithm

被引：6

作者：

Dai S.-S. ^{[1
]}

Liu J.-S. ^{[1
]}

Xiang H.-Y. ^{[1
]}

Du Z.-H. ^{[1
]}

Liu Q. ^{[1
]}

机构：

[1] Chongqing Key Laboratory of Signal and Information Processing, Chongqing University of Posts and Telecommunications, Chongqing

来源：

Liu, Jin-song | 1600年 / Springer Verlag卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Image reconstruction - Infrared imaging - Optical resolving power - Edge detection - Image enhancement;

D O I：

10.1007/s11801-014-4067-x

中图分类号：

学科分类号：

摘要：

Aiming at these disadvantages like lack of details, poor contrast and blurry edges of infrared images reconstructed by traditional controllable microscanning super-resolution reconstruction (SRR), this paper proposes a novel algorithm, which samples multiple low-resolution images (LRIs) by uncontrollable microscanning, and then uses LRIs as chromosomes of genetic algorithm (GA). After several generations of evolution, optimal LRIs are got to reconstruct the high-resolution image (HRI). The experimental results show that the average gradient of the image reconstructed by the proposed algorithm is increased to 1.5 times of that of the traditional SRR algorithm, and the amounts of information, the contrast and the visual effect of the reconstructed image are improved. © 2014, Tianjin University of Technology and Springer-Verlag Berlin Heidelberg.

引用

页码：313 / 316

页数：3

共 12 条

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