Image denoising algorithm based on improved wavelet threshold

In order to overcome the problems of fixed deviation and discontinuity of the traditional wavelet threshold function, an improved wavelet threshold function is proposed. Compared with soft threshold method, hard threshold method, Birge MassArt strategy soft threshold method, half soft threshold method and half soft threshold combined mean filtering method, the peak signal-to-noise ratio is increased by 1.2% ~ 6.9%, and the root mean square error is reduced by 4.8% ~ 22.4%. In the image mixed with Gaussian noise, salt and pepper noise and speckle noise, the combination method of improved wavelet threshold function and adaptive median filter is better than the single adaptive median filter, the peak signal-to-noise ratio is increased by 3 dB, and the root mean square error is reduced by 27%. The results show that the algorithm effectively improves the denoising effect of Gaussian noise image, and the combined denoising method has a better effect on the removal of mixed noise in the image.