PROJECTION-BASED SPATIALLY ADAPTIVE RECONSTRUCTION OF BLOCK-TRANSFORMCOMPRESSED IMAGES

At the present time, block-transform coding is probably the most popul ar approach for image compression, For this approach, the compressed i mages are decoded using only the transmitted transform data, In this p aper, we formulate image decoding as an image recovery problem, Accord ing to this approach, the decoded image is reconstructed using not onl y the transmitted data but, in addition, the prior knowledge that imag es before compression do not display between-block discontinuities. A spatially adaptive image recovery algorithm is proposed based on the t heory of projections onto convex sets. Apart from the data constraint set, this algorithm uses another new constraint set that enforces betw een-block smoothness, The novelty of this set is that it captures both the local statistical properties of the image and the human perceptua l characteristics, A simplified spatially adaptive recovery algorithm is also proposed, and the analysis of its computational complexity Is presented, Numerical experiments are shown that demonstrate that the p roposed algorithms work better than both the JPEG deblocking recommend ation and our previous projection-based image decoding approach.