Image Enhancement of Motion Blur Based on Chaos Quantum Algorithm

Authors

  • Yanyan Zhao School of Mathematics and Computer, Tongling University, Tongling 244000, China

Abstract

The enhancement of motion-blurred images requires a local optimization solution; hence, a method based on the Chaos Quantum algorithm is designed. The degradation and noise functions are superposed to obtain the degraded image, the quantum particles are updated in the chaotic system, the adaptive denoising algorithm is used to denoise the moving image, the two-stage strategy and popular sorting are used to segment the moving fuzzy image, and the moving image is reconstructed by the chaotic quantum algorithm to improve the moving fuzzy image. The experimental results show that under the influence of strong noise, it has a higher peak signal-to-noise ratio, and the contrasts and details in the image are significantly improved. Compared with the original image, the standard deviation and information entropy of the enhanced image are significantly improved, which shows that the proposed method performs well and can make a significant improvement to motion-blurred images.

Keywords: Chaos Quantum algorithm, motion-blurred image, enhance, noise, degradation

Cite As

Y. Zhao, "Image Enhancement of Motion Blur Based on Chaos Quantum Algorithm", Engineering Intelligent Systems, vol. 30 no. 2, pp. 139-148, 2022.



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Published

2022-03-01

Issue

Vol. 30 No. 2 (2022): International Journal of Engineering Intelligent Systems

Section

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