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Image denoising method based on improved wavelet threshold algorithm
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AI
DOI：10.1007/s11042-024-18197-w.png)
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Abstract
En 中文
In order to achieve image denoising in high-noise environment, this paper proposes an image denoising algorithm based on improved wavelet thresholding algorithm.The algorithm first improves the problem of fixed threshold.Secondly, an improved wavelet threshold function is proposed for the traditional hard and soft threshold function.Finally, the combination of improved threshold function and threshold can improve the accuracy of wavelet threshold judgment, and realize the effective separation of image and noise. Experimental results show that the proposed algorithm can not only effectively remove image noise in noisy environment, but also obtain higher(Peak signal-to-noise ratio, PSNR) and smaller (Mean Squared Error, MSE).
Keywords:
Wavelet transform
Threshold function
Image denoising
PSNR
MSE
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W