A new deblocking algorithm based on feature analysis in wavelet domain

In this paper, a new wavelet-based deblocking algorithm is proposed. It sufficiently utilizes blocking-artifact features in wavelet domain. After the wavelet transform, the blocking artifacts appear as horizontal line-shape effect in high-low subband, vertical line-shape effect in low-high subband and grid-shape effect in high-high subband. Adaptive operators for different subbands can be computed based on the wavelet coefficients at these locations. They are applied to suppress blocking effects below the visual scope. The new method is nonlinear, computationally efficient and spatially adaptive. It can significantly reduce blocking artifacts while preserving edge and texture information. Experimental results show that the proposed algorithm has low computational cost and achieves improved image quality in both subjective and objective measurement.