Deep Video Compression for P-frame in Sub-sampled Color Spaces
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | 2022 IEEE International Symposium on Circuits and Systems (ISCAS) |
Publisher | Institute of Electrical and Electronics Engineers, Inc. |
Pages | 3200-3204 |
ISBN (electronic) | 9781665484855, 978-1-6654-8484-8 |
ISBN (print) | 978-1-6654-8486-2 |
Publication status | Published - 2022 |
Publication series
Name | Proceedings - IEEE International Symposium on Circuits and Systems |
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ISSN (Print) | 0271-4310 |
ISSN (electronic) | 2158-1525 |
Conference
Title | 55th IEEE International Symposium on Circuits and Systems (ISCAS 2022) |
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Location | The Austin Hilton (Hybrid) |
Place | United States |
City | Austin |
Period | 28 May - 1 June 2022 |
Link(s)
Abstract
In this paper, we propose a deep video compression method for P-frame in sub-sampled color spaces regarding the YUV420, which has been widely adopted in many state-of-art hybrid video compression standards, in an effort to achieve high compression performance. We adopt motion estimation and motion compression to facilitate the inter prediction of the videos with YUV420 color format, shrinking the total data volume of motion information. Moreover, the motion compensation module on YUV420 is cooperated to enhance the quality of the compensated frame with the consideration of the resolution alignment in the sub-sampled color spaces. To explore the cross-component correlation, the residual encoder-decoder is accompanied with two head-branches and color information fusion. Additionally, a weighted loss emphasizing more on the Y component is utilized to enhance the compression efficiency. Experimental results show that the proposed method can realize 19.82% bit rate reductions on average compared to the deep video compression (DVC) method in terms of the combined PSNR and predominant gains on the Y component.
Research Area(s)
- Deep learning, learned video compression, P-frame, sub-sampled color spaces
Citation Format(s)
Deep Video Compression for P-frame in Sub-sampled Color Spaces. / Lin, Rongqun; Zhang, Pingping; Wang, Meng et al.
2022 IEEE International Symposium on Circuits and Systems (ISCAS). Institute of Electrical and Electronics Engineers, Inc., 2022. p. 3200-3204 (Proceedings - IEEE International Symposium on Circuits and Systems).
2022 IEEE International Symposium on Circuits and Systems (ISCAS). Institute of Electrical and Electronics Engineers, Inc., 2022. p. 3200-3204 (Proceedings - IEEE International Symposium on Circuits and Systems).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review