关键词: 多聚焦图像融合, 提升静态小波变换, 联合稀疏表示, 结构组稀疏表示, 拉普拉斯能量和, 匹配度

Abstract: An image fusion algorithm based on Lifting Stationary Wavelet Transform(LSWT) and joint structural group sparse representation was proposed to restrain pseudo-Gibbs phenomenon created by conventional wavelet transform in multi-focus image fusion, overcome the defect that the fusion method with conventional sparse representation was likely to lead textures, edges, and other detail features of fused images to the tendency of smoothness, and improve the efficiency and quality of multi-focus image fusion. Firstly, lifting stationary wavelet transform was conducted on the experimental images, different fusion modes were adopted according to the respective physical characteristics of low frequency coefficients and high frequency coefficients after decomposition. When selecting coefficients of low frequency, the scheme of coefficient selection based on joint structural group sparse representation was adopted; When selecting coefficients of high frequency, the scheme of coefficient selection based on Directional Region Sum Modified-Laplacian (DRSML) and matched-degree was adopted. Finally, ultimate fusion image was obtained by inverse transform. According to the experiment results, the improved algorithm can effectively improve such image indicators as mutual information and average gradient, keep textures, edges, and other detail features of images intact, and produce better image fusion effects.

Key words: multi-focus image fusion, Lifting Stationary Wavelet Transform (LSWT), Joint Sparse Representation (JSR), structural group sparse representation, Sum Modified-Laplacian (SML), matched-degree