Adaptive Wavelet Domain Filter for Versatile Video Coding (VVC)

By Suhong Wang, Xianguo Zhang, Shanshe Wang, Siwei Ma, Wen Gao. Data Compression Conference, 2019

1,138 citations recorded by the source corpus.

Owing to the ability of removing compression artifacts, extensive in-loop filters have been proposed for video coding standards. They are performed after the reconstruction of all coding units (CUs), however, none of them has been taken into account in the mode decision when coding each CU. To address this issue and make the rate-distortion optimization (RDO) more precise for each CU, we introduce a low-pass filter when checking the rate-distortion cost after the reconstruction of each CU. Specifically, based on Haar wavelet, the reconstructed block is transformed to the frequency domain, and then an adaptive wavelet domain filter (AWF) is proposed to suppress the quantization noises in coded blocks. To be adaptive, the filter strength varies from CU to CU according to the texture complexity and quantization parameters (QPs). Experimental results show that the proposed method can reduce the compression artifacts and improve both the objective and subjective quality.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/0e75de5761fa9cd665886e957a21ce4e43fd6e75

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In Computer Vision and Pattern Recognition

1. Anson Ho
2. Mohsen Guizani
3. Marius Hobbhahn
4. Tamay Besiroglu
5. Jaime Sevilla
6. Lennart Heim
7. Pablo Villalobos

Citations in the corpus

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