THE STUDY OF FUSION AND SUPER-RESOLUTION RECONSTRUCTION BASED ON PARTICLE SWARM OPTIMIZATION AND WAVELET ANALYSIS

被引：0
|
作者：
Wang, Senhua [1 ]
Ma, Zhenli [2 ]
Wan, Ping [1 ]
Cui, Hao [1 ]
Liu, Bo [1 ]
机构：
[1] Army Logist Univ PLA, Mil Logist Dept, Chongqing, Peoples R China
[2] Army Logist Univ PLA, Oil Dept, Chongqing, Peoples R China
来源：
2017 14TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP) | 2017年
基金：
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词：
Wavelet Analysis; The Particle Swarm; Super-Resolution Reconstruction;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The image super-resolution reconstruction can be widely used in military, medicine, transportation, etc. Due to the unfavorable factors, such as noises and obstacles, of the low resolution images, the influence of noises or the obstacles can be amplified by the super-resolution reconstruction. For this reason, the wavelet analysis were combined with the particle swarm optimization algorithm in this paper. Through the wavelet and particle swarm de-noising and registration on the original low resolution images, the super resolution reconstruction image can be obtained after the image fusion, and the results are better than traditional methods.
引用
收藏
页码：201 / 205
页数：5
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