Image denoising using multi-scale thresholds method in the wavelet domain

Images often contain noise due to the capturing devices, environment and even human errors. For the image further processing, compression, fractal and so on, the image denoising is necessary. Wavelet analysis plays a very important role in the image denoising. In this paper, we improve the wavelet thresholding method by using multi-scale thresholds and a new thresholding function. Also, in case of large noise, a median filter is suggested to be used at last. Based on Lipschitz exponent and wavelet transform, we theoretically give the multi-scale thresholds. In order to obtain a better denoising result, We also present a new thresholding function instead of the hard or soft thresholding function. Experiment results show that our improved method gives a higher PSNR and has less visual artifacts compared with other methods.