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- Title
An AK-BRP dictionary learning algorithm for video frame sparse representation in compressed sensing.
- Authors
Qian, Yang; Li, Lei; Yang, Zhenzhen; Zhou, Feifei
- Abstract
Sparsifying transform is an important prerequisite in compressed sensing. And it is practically significant to research the fast and efficient signal sparse representation methods. In this paper, we propose an adaptive K-BRP (AK-BRP) dictionary learning algorithm. The bilateral random projection (BRP), a method of low rank approximation, is used to update the dictionary atoms. Furthermore, in the sparse coding stage, an adaptive sparsity constraint is utilized to obtain sparse representation coefficient and helps to improve the efficiency of the dictionary update stage further. Finally, for video frame sparse representation, our adaptive dictionary learning algorithm achieves better performance than K-SVD dictionary learning algorithm in terms of computation cost. And our method produces smaller reconstruction error as well.
- Subjects
IMAGE processing; IMAGE reconstruction; COMPRESSED sensing; RANDOM projection method; SINGULAR value decomposition
- Publication
Multimedia Tools & Applications, 2017, Vol 76, Issue 22, p23739
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-016-4134-3