L1-L1 norm-based convolutional sparse coding via Anderson-accelerated Douglas-Rachford splitting

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dc.contributor.authorTake, Hiroto
dc.contributor.authorFurusho, Riku
dc.contributor.authorWoraratpanya, Kuntpong
dc.contributor.authorKuroki, Yoshimitsu
dc.date.accessioned2026-08-06T10:54:42Z
dc.date.available2026-08-06T10:54:42Z
dc.date.issued2026-02-27
dc.description.abstractConvolutional Sparse Coding (CSC) represents a signal through the convolution of dictionary filters and sparse coefficients. While the Alternating Direction Method of Multipliers (ADMM) has conventionally been used to solve CSC problems, recent studies have demonstrated that Douglas-Rachford (DR) splitting can achieve faster convergence. In this study, we propose an accelerated CSC algorithm by applying Anderson Acceleration to the DR splitting method. Experimental results demonstrate that the proposed method significantly improves convergence speed compared to standard DR splitting.
dc.identifier.citationProceedings of SPIE the International Society for Optical Engineering, 14072, 2026
dc.identifier.doi10.1117/12.3102610
dc.identifier.issn0277786X
dc.identifier.other2-s2.0-105038729328
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/17897
dc.sourceProceedings of SPIE the International Society for Optical Engineering
dc.subjectAnderson Acceleration
dc.subjectConvolutional Sparse Coding
dc.subjectDouglas-Rachford Splitting
dc.titleL1-L1 norm-based convolutional sparse coding via Anderson-accelerated Douglas-Rachford splitting
dc.typeConference Paper

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