Image mosaic based on SIFT and morphological component analysis

摘要

Due to traditional image mosaicing resulting in remarkable seams, we propose a novel method to address the problem to make the result more smooth. The approach is constructed based on SIFT algorithm and morphological component analysis(MCA) over trained dictionaries. The two cores of image mosaic are image registration and fusion. First, feature points are extracted by the SIFT algorithm which are used to realize image registration. Then we employ K-SVD algorithm to train an overcomplete dictionary based on the original images and use the MCA to decompose the images so that the decomposed components cartoon, texture can be used to fuse images, respectively. This method leads to a state-of-the-art mosaic performance, meanwhile, the noise contained by original images can also be filtered.