This paper introduces a new practical algorithm called tree-based multiscale pursuit (TMSP) for sparse signal representation over redundant dictionary. The main contribution is the construction of the tree-structured multiscale dictionary which is based on the similarity of the atoms. The similarity is estimated by the distance of the atoms’ parameters. Owing to efficiently organizing the original dictionary, TMSP algorithm makes a good compromise between the high performance and efficient implementation, and can satisfy the users’ different performances requirements by simply stopping the pursuit at different levels of the tree. Moreover, the tree-structured multiscale dictionary requires no extra memory and is easier to be constructed when compared with the tree-structured dictionary used in the tree-based pursuit.
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