基于多尺度方向局部极值滤波和ASR的图像融合

摘要

为了更好地提取源图像的边缘和方向信息,充分利用边缘保持滤波器的保边缘特性和方向滤波器有效提取方向信息的能力,提出一种基于局部极值滤波和非下采样方向滤波器的多尺度方向局部极值滤波图像融合方法.源图像经多尺度方向局部极值滤波,得到低频子带以及一系列的高频方向细节子带,对低频子带系数提出一种基于自适应稀疏表示(ASR)的融合规则,采用空间频率与l1范数相结合的策略得到融合的稀疏表示系数,对高频方向细节子带系数提出一种基于改进拉普拉斯能量和匹配度的选择与加权平均相结合的融合策略.实验结果表明,本方法能够有效提取源图像的边缘等细节信息,融合结果对比度更高,具有更好的主观视觉效果,其客观评价指标也优于传统的图像融合方法.%In order to extract the edge and directional information of the source images effectively,a multiscale direc-tional local extrema filter image fusion algorithm based on local extrema and nonsubsampled directional filter bank is proposed.The proposed method takes full use of the feature of edge -preserving filter and the ability of the nonsub-sampled directional filter bank,which can preserve the edges and extracts the directional information of the source im-ages.The low -frequency subbands and the high -frequency directional detail subbands are obtained by decomposing the source images.The low -frequency subband coefficients are fused by an adaptive sparse representation(ASR) rule combined spatial frequency and l1 norm.The high -frequency directional detail subband coefficients are fused by an adaptive selection and average strategy based on the match degree of the sum of modified Laplacian.Experimental results show that the proposed method could extract the detail information of the source images such as edges.The fu-sion results have higher contrast and better subjective visual effect.The proposed method also outperforms the conven-tional image fusion methods in terms of the objective evaluation criteria.