boundary matching algorithm

A challenging aspect of video error concealment (VEC) is reducing blockiness around the missing region. In this paper, we have devised a novel method for calculating the boundary matching distortion based on the edge direction surrounding the lost area to deal with this problem. After detecting the corresponding slice’s erroneous Macroblock (MB), it is divided into four 8×8 pixels sub-blocks. Then, the gradient of outer boundary pixels is derived and determines each side’s smoothness, which is further used for drawing the hypothetical line. Furthermore, this paper proposes a novel optimization-based model that can accurately measure boundary matching error for loss recovery. We observe better results for our proposed technique than other related VEC algorithms in terms of PSNR and SSIM. The proposed algorithm improves the average PSNR by 1.09 dB and increases the average SSIM by 0.0135 at the packet loss rate of 10%. In addition, for a PLR of 20%, the PSNR is increased by 1.28 dB, and the SSIM enhancement is 0.019. This algorithm is slightly more computationally complex than the compared methods, but it is still acceptable. Thus, by adding a few computations to the video decoder, the proposed method maintains the quality of the video, especially in the rough, damaged regions of a decoded frame.