FUSION OF DEFOCUSED IMAGES USING TRANSFORMS WITH SEGMENTATION

Abstract

This paper is concentrated on the improvement of data fusion techniques, which is applied on out-of-focused images. Segmentation is first employed to enhance the image features. An image transform is then applied to fuse the source images. In segmentation processes, quadtree and edge detection techniques are used. In quadtree, regions with image detail will be segmented into blocks with smaller size, and the background of the image will be assigned with larger block size. In edge detection, apparent objects in the image can be extracted. Image feature description is then made easy. After the preprocessing, those salient features in the image such as edges, lines and region boundaries will be selected as part of fused images. The rest of the regions without significant features are further processed using wavelet or DCT transforms. The transform coefficients from different sources are then appropriately combined. The final image is obtained by taking the inverse transform of the fused coefficients. Simulation results will demonstrate that our approaches will have better quality and efficiency.