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- Title
Gray Image Denoising Based on Array Stochastic Resonance and Improved Whale Optimization Algorithm.
- Authors
Huang, Weichao; Zhang, Ganggang; Jiao, Shangbin; Wang, Jing
- Abstract
Aiming at the poor effect of traditional denoising algorithms on image enhancement with strong noise, an image denoising algorithm based on improved whale optimization algorithm and parameter adaptive array stochastic resonance is proposed in the paper. In this algorithm, through dimensionality reduction scanning, coding, modulation and other processing, the noise-containing gray image becomes a one-dimensional aperiodic binary pulse amplitude modulation signal suitable for a bistable stochastic resonance model. Then, the traditional whale optimization algorithm is improved in the initial solution distribution, global search ability and population diversity generalization. The improved whale optimization algorithm is applied to select the parameters of the stochastic resonance, which effectively improves the parameters self-adaptive of the array stochastic resonance model. Finally, the denoised image is obtained by demodulating, decoding and anti-scanning the stochastic resonance output. The experimental results show that compared with the array stochastic resonance method with fixed parameters and the classical image denoising method, the algorithm proposed in this paper has better performance in terms of visual effect and peak signal-to-noise ratio index, which proves the advantages and effective application of the method in image denoising.
- Subjects
STOCHASTIC resonance; IMAGE denoising; GRAY codes; PULSE amplitude modulation; MATHEMATICAL optimization; SIGNAL-to-noise ratio; IMAGE intensifiers
- Publication
Applied Sciences (2076-3417), 2022, Vol 12, Issue 23, p12084
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app122312084