Non-subsampled contourlet transform algorithm to promote detail information capturing ability
提升细节捕捉能力的非下采样轮廓波变换

The NSP (multi-scale decomposition method) of the traditional NSCT (non-subsampled contourlet transform) algorithm has a poor detail information capturing ability and when applied to image fusion it causes a loss of image details. In this paper, we present an improved NSCT algorithm. Different from the traditional NSCT algorithm, we adopt the non-subsampled morphological wavelet decomposition, which has a better detail capture capability, to realize a multi-scale decomposition of the source image and replacing the NSP decomposition. The source images are decomposed into four parts: low-frequency, horizontal high-frequency, vertical high-frequency, and diagonal high-frequency. Afterwards, the improved NSCT decomposition on high frequencies using the NDFB (non-subsampled directional filter) for multiple directions of decomposition is realized. Our experiments show that, compared with traditional algorithms, this algorithm has a better detail capturing ability, its image fusion effect is better under the same fusion rules, and all fusion indexes are improved. Among them, the average gradient is increased by 10%. This effective image fusion algorithm can be easily realized and widely used in multi-resolution image fusion.