Image fusion combining contrast pyramid with clonal selection based on weighed Wedgelets

被引:0
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作者
Institute of Intelligent Information Processing, Xidian University, Xi'an 710071, China [1 ]
机构
来源
Hsi An Chiao Tung Ta Hsueh | 2007年 / 10卷 / 1170-1174期
关键词
Algorithms - Data structures - Mathematical transformations - Wavelet transforms;
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学科分类号
摘要
In order to improve the effect of fusion images, a novel image scheme is proposed, which uses weighed wedgelets and wavelet transform to fuse the details in corresponding image sequences of multiple scale obtained by the contrast pyramid data structure, and trains the weight by utilizing clonal selection algorithm. The proposed method improves the visual effects such as retaining the details and textures effectively and keeping the information entropy values of fused images at a high level. Simulation results show that compared with the conventional wavelet transform and wedgelets method, the average grad values of the image pixel is increased averagely by about 0.31 and 3.27 respectively, and 2.27 and 3.93 for the standard differences values.
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