Wavelet Denoising of Images Corrupted by Non-uniform Noise
Xiuying Li · Modern Electronic Technique · 2005
Most methods assume that the noise is spatially stationary additive white Gaussian noise (AWGN).We aim at noise that is spatially nonspatially stationary AWGN′s,and give pointwise thresholding method based on the neighborhood estimations in this text;then extend joint wavelet denoising method using multiple copies corrupted by spatially stationary AWGN′s to nonspatially stationary case.Image thresholding is selfregulating Bayes function which base on noise variances and signal variances.We combine thresholding and average method for multiple copies corrupted by nonspatially stationary AWGN′s,which weighted value is reckoned by noise variances,and compare two different pointwise weighted averages in image and wavelet domain.