基于非下采样轮廓波变换和压缩感知的图像融合方法

Fusion technique for images based on non-subsampled contourlet transform and compressive sensing

针对基于非下采样轮廓波变换(NSCT)的图像融合算法存在计算复杂度较高的问题,提出一种基于NSCT和压缩感知的图像融合方法.首先根据压缩感知理论的特点将其应用于图像融合领域,并采用Min-TV的方法重构图像;然后对NSCT进行分解,其计算量较大的带通子带系数采用基于压缩感知理论的图像融合方法;最后对低通融合图像和带通融合图像进行NSCT逆变换,得到最终的融合图像.通过仿真实验,从主观感知和客观数据的对比分析上验证了所提出方法的有效性.

For the calculation complexity problem of image fusion based on non-subsampled contourlet transform（NSCT）, an algorithm of combining the NSCT with compressive sensing（CS） is presented. Firstly, based on the characters of the CS theory in image fusion, the method of rebuilding the images is modified. Then the NSCT is used to decompose the images, and the image fusion approach based on CS is applied to the decomposed band-pass sub-band coefficients which are featured with high calculation complexity to obtain the band-pass fusion image. Finally, the inverse transform of NSCT is used to fuse the low-pass fusion image and band-pass fusion image to gain the final fusion image. The simulation results show the effectiveness of the proposed approach.