This paper proposes a low-complexity spatial-domain Error Concealment (EC) algorithm for recovering consecutive blocks error in still images or Intra-coded (I) frames of video sequences. The proposed algorithm works w...This paper proposes a low-complexity spatial-domain Error Concealment (EC) algorithm for recovering consecutive blocks error in still images or Intra-coded (I) frames of video sequences. The proposed algorithm works with the following steps. Firstly the Sobel operator is performed on the top and bottom adjacent pixels to detect the most likely edge direction of current block area. After that one-Dimensional (1D) matching is used on the available block boundaries. Displacement between edge direction candidate and most likely edge direction is taken into consideration as an important factor to improve stability of 1D boundary matching. Then the corrupted pixels are recovered by linear weighting interpolation along the estimated edge direction. Finally the interpolated values are merged to get last recovered picture. Simulation results demonstrate that the proposed algorithms obtain good subjective quality and higher Peak Signal-to-Noise Ratio (PSNR) than the methods in literatures for most images.展开更多
基金Supported by Doctor’s Foundation in Natural Science of Hebei Province of China (No.B2004129).
文摘This paper proposes a low-complexity spatial-domain Error Concealment (EC) algorithm for recovering consecutive blocks error in still images or Intra-coded (I) frames of video sequences. The proposed algorithm works with the following steps. Firstly the Sobel operator is performed on the top and bottom adjacent pixels to detect the most likely edge direction of current block area. After that one-Dimensional (1D) matching is used on the available block boundaries. Displacement between edge direction candidate and most likely edge direction is taken into consideration as an important factor to improve stability of 1D boundary matching. Then the corrupted pixels are recovered by linear weighting interpolation along the estimated edge direction. Finally the interpolated values are merged to get last recovered picture. Simulation results demonstrate that the proposed algorithms obtain good subjective quality and higher Peak Signal-to-Noise Ratio (PSNR) than the methods in literatures for most images.
