Multimodal Medical Image Fusion in Modified Sharp Frequency Localized Contourlet Domain

Abstract

As a novel of multi-resolution analysis tool, the modified sharp frequency localized contour let transforms (MSFLCT) provides flexible multiresolution, anisotropy, and directional expansion for medical images. In this paper, we proposed a new fusion rule for multimodal medical images based on MSFLCT. The multimodal medical images are decomposed by MSFLCT. For the high-pass sub band, the weighted sum modified laplacian (WSML) method is used for choose the high frequency coefficients. For the low pass sub band, the maximum local energy (MLE) method is combined with "region" idea for low frequency coefficient selection. The final fusion image is obtained by applying inverse MSFLCT to fused low pass and high pass sub bands. Abundant experiments have been made on groups of multimodality datasets, both human visual and quantitative analysis show that the new strategy for attaining image fusion with satisfactory performance.