Block Level Multi-Focus Image Fusion Using Wavelet Transform

Due to importance and verity of usage image fusion has become a valuable field of research. Improving the quality of sensors to collect all information about a scene has technical limitations. Image fusion is applied to integrate multiple images of the scene having focus on different objects and to present cumulative clear view of the scene. Discrete wavelet transform is applied on every image block with the assumption that images have focused or blurred areas rather than individual pixels. Prewitt edge detector is applied on wavelet coefficients to find clearer blocks from source images. A decision map is constructed for clear blocks from each image. Using this decision map clearer non-boundary blocks are copied from the source images to the resulting fused image, whereas boundary blocks are fused using ‘Maximum Wavelet Coefficients Method’. The proposed scheme assures better performance when put to test using image quality evaluation metrics.