Noise estimation for blocking artifacts reduction in DCT coded images

Abstract

This paper proposes a postprocessing algorithm that can reduce the blocking artifacts in discrete cosine transform (DCT) coded images. To analyze blocking artifacts as noise components residing across two neighboring blocks, we use 1-D pixel vectors made of pixel rows or columns across two neighboring blocks. We model the blocky noise in each pixel vector as a shape vector weighted by the boundary discontinuity. The boundary discontinuity of each vector is estimated from the difference between the pixel gradient across the block boundary and that of the internal pixels. We make minimum mean squared error (MMSE) estimates of the shape vectors, indexed by the local image activity, based on the noise statistics prior to postprocessing. Once the estimated shape vectors are stored in the decoder, the proposed algorithm eliminates the noise components by simply subtracting from each pixel vector an appropriate shape vector multiplied by the boundary discontinuity. The experimental results show that the proposed algorithm is highly effective in reducing blocking artifacts in both subjective and objective viewpoints, at low computational burden.