基于空间原子特征匹配的多聚焦图像融合

针对多聚焦图像融合,提出一种新颖的基于空间原子特征匹配的融合算法,该算法利用匹配跟踪信号分解算法,有选择性地提取出各个输入源图像的高频成分,使得融合生成的目标图像具有最丰富的细节特征,且不会出现波纹及方块效应.实验结果表明,利用该算法所获得的融合图像能够保留输入源图像中大部分主要边缘特征,主观视觉效果与客观评价指标均优于传统的小波图像融合算法或空间频率法.

Multifocus Image Fusion Through Spatial Atom Matching

Aiming at multi-focus image fusion,a new image fusion algorithm based on spatial atom structure matching is proposed,it can extract distinctive high frequency components selectively from each input registered image,exploiting matching pursuit signal decomposition.In the result,the fused image has most profound details,without rings or block artifacts.Experimental results show that the algorithm can achieve better fusion effect than the traditional wavelet image fusion method or spatial frequency method,whether from subjective visual effect or objective metric.