Dictionary learning in convolutional sparse representation

Lijun Xu; Ying Wang; Yijia Zhou

doi:10.1117/12.2672444

28 March 2023 Dictionary learning in convolutional sparse representation

Lijun Xu, Ying Wang, Yijia Zhou

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 125973H (2023) https://doi.org/10.1117/12.2672444
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

In this paper, we present a new convolution form based on dictionary learning and study its sparse version based on Convolution Dictionary Learning (CDL). An effective algorithm for learning sparse convolution features is proposed by combining Alternating Direction Multiplier Method (ADMM) and Fast Iterative Shrinkage Threshold Algorithm (FISTA). Through numerical experiments, we show that the proposed algorithm can not only lead to faster convergence speed, but also produce better sparse features.

Citation Download Citation

Lijun Xu, Ying Wang, and Yijia Zhou "Dictionary learning in convolutional sparse representation", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 125973H (28 March 2023); https://doi.org/10.1117/12.2672444

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KEYWORDS

Associative arrays

Convolution

Matrices

Data modeling

Image processing

Shrinkage

Feature extraction

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