Restoration of wavelet-compressed images using adaptively masking smoothness constraints

The wavelet-compressed images suffer from coding artifacts, such as ringing and blurring, due to quantizing the transform coefficients. To reduce such coding artifacts, we propose a new image enhancement algorithm based on regularized iterative image restoration. The proposed algorithm uses multiple constraints to simultaneously suppress the coding artifacts and preserve the original high-frequency components. We also present the hierarchical implementation for the proposed algorithm. Spatial adaptivity plays a role in keeping the edge from spreading out to other pixels which have different directional characteristics