Multilevel Medical Image Fusion using Segmented Image by Level Set Evolution with Region Competition

In this paper, a region level based image fusion technique, using wavelet transform, has been implemented and analyzed. The proposed methodology considers regions as the basic feature for representing images and uses region properties for extracting the information from them. A segmentation algorithm is proposed for extracting the regions in an effective way for fusing the images. The fusion strategy uses multi-level decomposition of the images obtained using wavelet transform. By analyzing the images at multiple levels, the proposed method is able to extract finer details from them and in turn improves the quality of the fused image. The performance and relative importance of the proposed methodology is investigated using the mutual information criteria. Experimental results show that the proposed method improves the quality of the fused image significantly for both the normal and multifocused images