A Novel Medical Image Fusion Approach Based on Nonsubsampled Shearlet Transform

To solve the problems of blurring and blocking artifact in medical image fusion, a novel medical image fusion algorithm based on nonsubsampled shearlet transform (NSST) is proposed. Firstly, the source images are decomposed into low-frequency and high-frequency components by NSST transform. Secondly, the lowfrequency components are merged by a novel fusion technique, and the high-frequency components are merged utilizing the local coefficient energy rule. Finally, the fused medical image is obtained by performing the inverse nonsubsampled shearlet transform (INSST) on the merged components. The experiment is simulated on different medical images. The experimental results demonstrate that the proposed fusion approach can achieve superior performance in terms of the subjective and objective measurements.