Image Fusion Approach with NOISE REDUCTION USING GENETIC ALGORITHM & Sure-let Algorithm

Fusing information contained in multiple images plays an increasingly important role for quality inspection in industrial processes as well as in situation assessment for autonomous systems and assistance systems. The aim of image fusion in general is to use images as redundant or complementary sources to extract information from them image fusion in general is to use images as redundant or complementary sources to extract information from them image that is focused in all of its parts. The results show that Curvelet transform had been proven to be effective at detecting image activity along curves, and increasing the quality of the obtained fused images. GA shows more accurate results in image de-noising. We performed image fusion using Curvelet Transform with Genetic Algorithm and Sure-let algorithm for image denoising. This new method has reached an optimum fusion result. For the implementation of this proposed work we use the Image Processing Toolbox under Matlab Software.