An Efficient Adaptive Boundary Matching Algorithm for Video Error Concealment
This work addresses video quality degradation in decoders for applications like streaming over the Internet and wireless networks, representing an incremental improvement over prior error concealment techniques.
The paper tackles the problem of video error concealment in error-prone environments by proposing an adaptive boundary matching algorithm to recover damaged motion vectors, resulting in improved objective and subjective quality with average PSNR increases of up to 5.88 dB compared to existing methods.
Sending compressed video data in error-prone environments (like the Internet and wireless networks) might cause data degradation. Error concealment techniques try to conceal the received data in the decoder side. In this paper, an adaptive boundary matching algorithm is presented for recovering the damaged motion vectors (MVs). This algorithm uses an outer boundary matching or directional temporal boundary matching method to compare every boundary of candidate macroblocks (MBs), adaptively. It gives a specific weight according to the accuracy of each boundary of the damaged MB. Moreover, if each of the adjacent MBs is already concealed, different weights are given to the boundaries. Finally, the MV with minimum adaptive boundary distortion is selected as the MV of the damaged MB. Experimental results show that the proposed algorithm can improve both objective and subjective quality of reconstructed frames without any considerable computational complexity. The average PSNR in some frames of test sequences increases about 5.20, 5.78, 5.88, 4.37, 4.41, and 3.50 dB compared to average MV, classic boundary matching, directional boundary matching, directional temporal boundary matching, outer boundary matching, and dynamical temporal error concealment algorithm, respectively.