Region based Multimodality Image Fusion Method

This paper proposes a novel region based image fusion scheme based on high boost filtering concept using discrete wavelet transform. In the recent literature, region based image fusion methods show better performance than pixel based image fusion method. The graph based normalized cutest algorithm is used for image segmentation. Proposed method is a novel idea which uses high boost filtering concept to get an accurate segmentation using discrete wavelet transform. This concept is used to extract regions from input registered source images which is then compared with different fusion rules. The new MMS fusion rule is also proposed to fuse multimodality images. The different fusion rules are applied on various categories of input source images and resultant fused image is generated. Proposed method is applied on large number of registered images of various categories of multifocus and multimodality images and results are compared using standard reference based and nonreference based image fusion parameters. It has been observed from simulation results that our proposed algorithm is consistent and preserves more information compared to earlier reported pixel based and region based methods