Abstract not found

Methods like edge directed interpolation and projection onto convex sets (POCS) that are widely used for image error concealment to produce better image quality are complex in nature and also time consuming. Moreover, those methods are not suitable for real time error concealment where the decoder may not have sufficient computation power or done in online. In this paper, we propose a data-hiding scheme for error concealment of digital image. Edge direction information of a block is extracted in the encoder and is embedded imperceptibly into the host media using quantization index modulation (QIM), thus reduces work load of the decoder. The system performance in term of fidelity and computational load is improved using M-ary data modulation based on near-orthogonal QIM. The decoder extracts the embedded features (edge information) and those features are then used for recovery of lost data. Experimental results duly support the effectiveness of the proposed scheme.

Abstract—In this paper we propose a novel sequential error concealment algorithm for video and images based on sparse linear prediction. Block-based coding schemes in packet loss environment are considered. Images are modelled by means of linear prediction and missing macroblocks are sequentially reconstructed using the available groups of pixels. The optimal predictor coefficients are computed by applying a missing data regression imputation procedure with a sparsity constraint. Moreover, an efficient procedure for the computation of these coefficients based on an exponential approximation is also pro-posed. Both techniques provide high quality reconstructions and outperform the state-of-the-art algorithms both in terms of PSNR and MS-SSIM. Index Terms—Error concealment, block-coded images/video, convex optimization, missing data imputation, sparse represen-tation I.