A novel weighted boundary matching error concealment Schema for HEVC

Abstract

In this paper, a novel weighted boundary matching error concealment schema for HEVC is proposed, which is based on the CU depths and PU partitions in reference frame. Firstly, the information of CU depths in reference frames is used for lost slices. For each LCU in a lost slice, the LCUs surrounding to the co-located LCU are used to calculate summed CU-depth weight, which is used to determine the conceal order of each CU. Then, the co-located partition decision from the reference frame is adopted for PUs in each lost CU. The sequence of PUs to conceal is sorted based on the texture randomness index weight and the PU with the largest weight will be concealed next. Finally, the best estimated motion vector for the lost PU is selected for concealment. The experimental results show that our method achieves higher PSNR gains and has a better visual quality than the state-of-the-art methods.

Publication
2018 25th IEEE International Conference on Image Processing
Chuan Yan
Chuan Yan
PhD Student

I am a researcher interested in AI-assistant drawing techniques.

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