This study proposes an adaptive error concealment selection process in order to improve the quality of reconstructed images which have low computation complexity for multi-view video coding. In this study, the proposed algorithm uses the motion vector variances and texture histogram bins in the blocks neighboring the damaged block in order to define two correlations; the degree of motion and the degree of texture similarity. To increase the accuracy of the suitable EC for the damaged macro-block, these two correlations are used to select a suitable error concealment method for reconstructing the damaged macro-block through fuzzy reasoning. The motion degree indicates the motion complexity for the damaged macro-block, and the texture similarity degree indicates the spatial continuity between the damaged macro-block and its neighboring block. The proposed adaptive error concealment is selected to reduce concealing time on homogenous damaged blocks and to improve the reconstructed image quality on non-homogenous damaged blocks. The experiment results show that the proposed algorithm can reduce the concealing time by at least 1.16 s and can improve the peak signal-to-noise (PSNR) by 0.13 dB–2.44 dB and 0.11 dB–3.52 dB in the main views and auxiliary views, respectively. This proposed algorithm is suitable for the multi-view video transmission on the consumer electronic fields such as 3D mobile devices, 3D television.
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