Compressive sensing image recovery algorithm based on improved smoothed L0 norm

Youyu Zhao; Jiao Wang; Xiangmin Jia; Junjie Feng

doi:10.1117/12.3031366

19 July 2024 Compressive sensing image recovery algorithm based on improved smoothed L0 norm

Youyu Zhao, Jiao Wang, Xiangmin Jia, Junjie Feng

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 1318128 (2024) https://doi.org/10.1117/12.3031366
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

To obtain fast and accurate image recovery result, an image recovery algorithm based on the improved smoothed L0 norm is proposed in the article. Firstly, the negative exponential function called smoothed function can be used to approach L0 norm, the optimal value of the smoothed function is solved by constructing the sequence of control parameters. Secondly, the gradient projection algorithm can be used to solve the optimal value which recovery the sparse signal. Finally, a comparison correction step is added which can search according to the steepest descent direction to ensure the precise recovery of sparse signal can be obtained. Experimental results express the performance of the proposed algorithm is superior to traditional methods.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Youyu Zhao, Jiao Wang, Xiangmin Jia, and Junjie Feng "Compressive sensing image recovery algorithm based on improved smoothed L0 norm", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 1318128 (19 July 2024); https://doi.org/10.1117/12.3031366

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KEYWORDS

Reconstruction algorithms

Image restoration

Compressed sensing

Matrices

Signal processing

Mathematical optimization

Surface plasmons

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