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17 May 2022 Research on fixing the best parameter to image denoising by proximity algorithms
Zirui He, Mingyi Zhang
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Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 122595R (2022) https://doi.org/10.1117/12.2639451
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China
Abstract
Algorithms play an extremely important role in daily life. Most algorithms have some basic custom parameters. When using the algorithm, the parameter value greatly affects the speed and optimal result of the algorithm. The purpose of this paper is to explore the ideas of efficient parameter adjustment and avoid spending much time on invalid experimental operations. In order to get closer to the current research frontier, this paper takes the proximity algorithm of the denoising image model as an example. This paper introduces the current hot image denoising and introduces the fixed point proximity algorithm of the experimental object. In this paper, the denoising effect of the model is tested by adding noise to grayscale images randomly. The compiler uses MATLAB to facilitate matrix calculation. The experimental study focuses on gradually reducing the optimal solution pair value range of the algorithm parameters from the perspective of the resulting image, the statistical regression analysis of the index, and the iterative convergence speed.
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Zirui He and Mingyi Zhang "Research on fixing the best parameter to image denoising by proximity algorithms", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 122595R (17 May 2022); https://doi.org/10.1117/12.2639451
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KEYWORDS
Denoising
Image filtering
Image denoising
Digital filtering
Image processing
Error analysis
Data modeling
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