A rapid image decomposition and reconstruction method based on non-subsampled shearlet transform is presented to improve the iterative filter efficiency in the process of dividing the sub-band images.All filters in the non-subsampled pyramid filter bank are convoluted based on the scales of the decomposition.Source image is filtered with convoluted results to acquire the sub-band images directly,which reduces the computational complexity of iterative filtering.To highlight the contour information,the low frequency coefficients are fused by using regional characteristics measuring method based on the standard deviation.The highest frequency coefficients are fused by using the maximum energy selection rule;the other high frequency coefficients are fused by combining sum modified-Laplacian(SML) with gradient features,which highlights the edge information of the target plume.Experimental results show that the subjective visual effect of the fused images is well,which can reflect the thermal plume’s temperature distribution obviously.Through several objective evaluation indexes,the proposed fusion method is superior to several traditional infrared and visible images fusion algorithms
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方静,罗高鹏.改进快速NSST的热烟羽红外与可见光图像融合[J].激光与红外,2017,47(7):914~920 FANG Jing, LUO Gao-peng. Infrared and visible images fusion of thermal plume based on rapid non-subsampled shearlet transform[J]. LASER & INFRARED,2017,47(7):914~920