A wavelet based adaptive regularization scheme for blind image restoration is presented. The degraded image is decomposed to obtain its wavelet coefficients in wavelet domain

and the image’s different frequency sub-bands are obtained also. Then

different adaptive regularization image restoration schemes are used in different sub-bands: removing blur in the low frequency sub-bands

while reducing noise and preserving edges in the high frequency sub-bands

and the algorithm finally obtains a restored image by adverse transforming. The experiments show that the MSE has a reduction of 1.60

while the SNR is increased by 1.76. It demonstrates that the blind image restoration method is more efficient compared with traditional space-adaptive regularization method.