结合随机投影和稀疏表示的图像融合方法

摘要/Abstract

摘要：

摘要：引入压缩感知理论解决基于稀疏表示的图像融合方法中融合质量和数据压缩问题，探索在达到一定融合质量的同时降低融合所需计算代价的方法.该方法首先利用随机投影对待融合图像数据进行压缩，再对压缩数据进行稀疏表示得到稀疏系数，根据融合影响因子确定融合稀疏表示系数获得融合图像.实验验证了该算法的合理性和有效性，及在较低压缩比下具有与传统方法可比拟的融合质量.

关键词: , 图像融合, 压缩感知, 随机投影, 稀疏表示

Abstract:

In order to reduce the computational cost while maintaining the sufficient fusion quality, a novel notion of image fusion approach was explored combining fusion with data compression based on compressed sensing. First, the sensing data was compressed by random projection. Then, the sparse coefficients were obtained on compressed samples by sparse representation. Finally, the fusion coefficients were combined with the fusion impact factor and the fused image was reconstructed from the combined sparse coefficients. Experimental results validate its rationality and effectiveness, which can achieve comparable fusion quality on less compressed sensing data.

Key words: image fusion, compressed sensing, random projection, sparse representation

中图分类号:

TN 919.85

王瑞，杜林峰，陈俊丽，万旺根. 结合随机投影和稀疏表示的图像融合方法[J]. 上海交通大学学报（自然版）, 2014, 48(10): 1421-1427.

WANG Rui,DU Linfeng,CHEN Junli,WAN Wanggen. Image Fusion Based on Random Projection and Sparse Representation[J]. Journal of Shanghai Jiaotong University, 2014, 48(10): 1421-1427.

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