针对基于非下采样轮廓波变换（NSCT）的压缩感知图像融合算法，存在融合图像局部细节信息表达不足的问题，提出一种基于NSCT 与离散小波变换（DWT）的压缩感知图像融合算法。首先，对图像进行NSCT 变换，得到低频系数和高频系数；然后，对高频系数进行压缩融合，并通过重构算法恢复融合的高频系数；而对低频系数，采取基于小波变换的融合方法；最后，对融合的高频系数和低频系数进行NSCT 逆变换，得到最终的融合图像。实验结果表明：本文算法使融合图像的质量，在主观和客观方面都得到了明显改善，最终的融合图像具有更多的细节特征和更清晰的边缘轮廓。

For lacking of details of image fusion based on compressed sensing of non-subsampled contourlet transform（NSCT）, an algorithm of image fusion based on compressed sensing of NSCT and discrete wavelet transform（DWT） is presented. First, the images are decomposed into high frequency coefficients and low frequency coefficients by NSCT. Then, the high frequency coefficients are compressed and fused. And the high frequency coefficients which are compressed and fused are reconstructed by a reconstructed algorithm. At the same time, the low frequency coefficients are fused based on DWT. Finally, the inverse transform of NSCT is used to recompose the high frequency coefficients and the low frequency coefficients to gain the final fusion image. Experimental results indicate that the proposed algorithm improves the fused images in terms of subjective and objective, and the fused images have more detail features and sharper edges.Q20131110