关键词: 压缩感知, 随机观测, 图像融合, 绝对值较大法

Abstract: Based on Compressed Sensing（CS）, a new image fusion method is presented. The new method can take reduced samples, and has the advantages of simple structure and easy implementation. The method decomposes two or more original images using wavelet transform, and gets the sparse matrix by the wavelet coefficient sparse representation, and fuses the sparse matrices with the coefficients absolute value maximum scheme. Randomly observed, it can receive the compressed sample. At the fusing end, the fusion image is recovered from the reduced samples by solving the optimization. The proposed method can construct the fusion image with less measurements because the wavelet coefficients are sparse presentation. Simulation results show the proposed method exhibits its superiority over the traditional method of the maximum absolute values fusion with the same sampling rates, and under the lower sampling, it can also achieve better fusion performance.

Key words: compressed sensing, randomly observed, image fusion, absolute value maximum scheme