Image fusion is the process of combining two or more images into a single image, which retains important features from each. Image fusion is one way to resolve the problem of un-focused images produced by non-professional camera users. Image fusion can be also used in remote sensing, robotics and medical application. In this thesis, a new image fusion technique for multi-focus images based on the SIFT (Scale Invariant Feature Transform) is proposed. The fusion procedure is performed by matching the image features of SIFT and then fusing two images by averaging that firstly decomposed using Discrete Wavelet Transform. Conditional sharpening is applied to get images better of quality. Experimental results show well in multi-focus image fusion.
Image fusion is the process of combining two or more images into a single image, which retains important features from each. Image fusion is one way to resolve the problem of un-focused images produced by non-professional camera users. Image fusion can be also used in remote sensing, robotics and medical application. In this thesis, a new image fusion technique for multi-focus images based on the SIFT (Scale Invariant Feature Transform) is proposed. The fusion procedure is performed by matching the image features of SIFT and then fusing two images by averaging that firstly decomposed using Discrete Wavelet Transform. Conditional sharpening is applied to get images better of quality. Experimental results show well in multi-focus image fusion.