Improved method for blocking-artifact reduction in block coded images in wavelet-transform domain

The paper describes an approach for improving blocking-artifact reduction techniques. We purpose some simple processing methods in the wavelet transform domain that can reduce the blocking effects in block-coded images. The properties of block-coding make the errors appear in two categories: blocky noise, which causes blocking effects, and granular (non-blocky) noise. Once a degraded image is decomposed into subbands by wavelet filters, most energy of the blocky noise exists on the predetermined block boundaries of their corresponding subbands. We can reduce the blocky noise by using an averaging filter, a median filter, or the linear minimum mean square error in each subband. After the blocky noise is reduced, the granular noise can be further decreased. The approach was tested by applying it to images (Lena, cameraman). Results presented provide an improvement in the processed image.