A New Approach for Medical Image Fusion Based on Laplacian Pyramid and GA

Abstract: Medical image fusion is a process which is used to minimize the redundancy while increasing the required information from input images acquired from different medical imaging sensors. Thus, the primary factor of fusion is to acquire a single enhanced and more informative image which can be employed for efficient analysis. This paper presented a hybridization approach used for medical image fusion. Initially, Laplacian Pyramid technique is utilized to extract the relevant features from set of images followed by resize operation. Afterward, Genetic Algorithm based upon swarm intelligence approach has applied over the extracted feature image for fusion. So as to ensure the efficiency of the proposed work, quantitative analysis of fused image is carried out under different performance metrics such as Entropy, Standard Deviation, Peak Signal to Noise Ratio, Structured Similarity and Measure of enhancement using MATLAB software. The experimental study concludes that proposed LP-GA approach outperforms the traditional techniques in terms of high quality and less noise.

Keywords: Medical Image Fusion, Laplacian Pyramid, Genetic Algorithm, DWT techniques, Fusion Metrics.