关键词: 非下采样剪切波变换, 区域特性, 高斯随机测量矩阵, 正交匹配追踪算法

Abstract: Aiming at the imaging characteristics of multi-focus image and multi-modality medical image, and considering with the properties of shearlet transform which can capture more directions and other geometric information of images, an image fusion method based on non-subsample shearlet transform using compressed sensing combined with regional characteristics is proposed. Multi-scale and multi-directional decompositions of source images are performed by non-subsampled shearlet trasnform. The decomposition of low frequency sub-band coefficients are merged by the regional energy and regional variance adaptive weighted fusion rule. Since the decomposed high frequency sub-band coefficients have high sparsity, it can be compressed by the Gaussian random measurement matrix, the fusion rule of the absolute value based on compressed sensing is adopted to fusion. Afterwards, it uses the orthogonal matching pursuit algorithm for reconstruction. And the fusion image is obtained by non-subsampled shearlet trasnform inverse transformation. The simulation results show that the image fusion effect of this method has better advantages in both subjective and objective evaluation than other traditional fusion methods.

Key words: non-subsample shearlet transform, regional characteristics, Gaussian random measurement matrix, orthogonal matching pursuit algorithm