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A wavelet denoising method of new adjustable threshold

For the problem of denoising incomplete phenomenon appeared in the existing wavelet threshold methods, a new kind of threshold function and denoising method of parameter adjustable wavelet threshold is proposed. The traditional hard threshold and soft threshold wavelet had problems such as continuity and constant deviation. Firstly, to construct a new threshold function and theoretically proves the superiority of this new threshold function, as long as choosing the suitable parameter, the new threshold function has a better denoising effect than traditional thresholding function. Secondly, to reduce the deviation between wavelet coefficients and the original, the threshold value is changed with the change of decomposition scale. The experimental results demonstrate that by using the proposed method, whether the Gaussian noise or impulse noise, the signal-to-noise ratio (SNR) of image and the peak signal to noise ratio (PSNR) of image can be greatly improved and the mean square error (MSE) of the image was reduced, the denoising effect is better than other algorithms.