Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models

Yuan Yang; Shuai Wan; Yanchao Gong; Kaifang Yang

doi:10.1109/ICIP.2016.7533158

Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models

Yuan Yang, Shuai Wan, Yanchao Gong, Kaifang Yang

School of Electronics and Information

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

In H.265/HEVC, the random-access prediction structure helps to increase the coding efficiency and provides the temporal scalability. However, the quantization parameter cascading (QPC) strategy being used is not optimized in terms of the rate-distortion performance. This paper analyzes the rate and distortion dependency between temporal layers, and proposes a PSNR metric-based distortion model and a piecewise rate model to optimize the QPC. Experimental results demonstrate that the proposed algorithm achieves an average APSNR gain of 0.12dB with the maximum APSNR gain being 0.37dB. Meanwhile, an up to 8.7% BD-rate reduction with the average BD-rate reduction being 3.3% can be obtained.

Original language	English
Title of host publication	2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
Publisher	IEEE Computer Society
Pages	4235-4239
Number of pages	5
ISBN (Electronic)	9781467399616
DOIs	https://doi.org/10.1109/ICIP.2016.7533158
State	Published - 3 Aug 2016
Event	23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States Duration: 25 Sep 2016 → 28 Sep 2016

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
Volume	2016-August
ISSN (Print)	1522-4880

Conference

Conference	23rd IEEE International Conference on Image Processing, ICIP 2016
Country/Territory	United States
City	Phoenix
Period	25/09/16 → 28/09/16

Keywords

H.265/HEVC
Quantization parameter cascading
Random access prediction structure
Rate and distortion dependency
Rate-distortion optimization

Access to Document

10.1109/ICIP.2016.7533158

Cite this

Yang, Y., Wan, S., Gong, Y., & Yang, K. (2016). Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (pp. 4235-4239). Article 7533158 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2016-August). IEEE Computer Society. https://doi.org/10.1109/ICIP.2016.7533158

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title = "Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models",

abstract = "In H.265/HEVC, the random-access prediction structure helps to increase the coding efficiency and provides the temporal scalability. However, the quantization parameter cascading (QPC) strategy being used is not optimized in terms of the rate-distortion performance. This paper analyzes the rate and distortion dependency between temporal layers, and proposes a PSNR metric-based distortion model and a piecewise rate model to optimize the QPC. Experimental results demonstrate that the proposed algorithm achieves an average APSNR gain of 0.12dB with the maximum APSNR gain being 0.37dB. Meanwhile, an up to 8.7% BD-rate reduction with the average BD-rate reduction being 3.3% can be obtained.",

keywords = "H.265/HEVC, Quantization parameter cascading, Random access prediction structure, Rate and distortion dependency, Rate-distortion optimization",

author = "Yuan Yang and Shuai Wan and Yanchao Gong and Kaifang Yang",

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Yang, Y, Wan, S, Gong, Y & Yang, K 2016, Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models. in 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings., 7533158, Proceedings - International Conference on Image Processing, ICIP, vol. 2016-August, IEEE Computer Society, pp. 4235-4239, 23rd IEEE International Conference on Image Processing, ICIP 2016, Phoenix, United States, 25/09/16. https://doi.org/10.1109/ICIP.2016.7533158

Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models. / Yang, Yuan; Wan, Shuai; Gong, Yanchao et al.
2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. IEEE Computer Society, 2016. p. 4235-4239 7533158 (Proceedings - International Conference on Image Processing, ICIP; Vol. 2016-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models

AU - Yang, Yuan

AU - Wan, Shuai

AU - Gong, Yanchao

AU - Yang, Kaifang

PY - 2016/8/3

Y1 - 2016/8/3

N2 - In H.265/HEVC, the random-access prediction structure helps to increase the coding efficiency and provides the temporal scalability. However, the quantization parameter cascading (QPC) strategy being used is not optimized in terms of the rate-distortion performance. This paper analyzes the rate and distortion dependency between temporal layers, and proposes a PSNR metric-based distortion model and a piecewise rate model to optimize the QPC. Experimental results demonstrate that the proposed algorithm achieves an average APSNR gain of 0.12dB with the maximum APSNR gain being 0.37dB. Meanwhile, an up to 8.7% BD-rate reduction with the average BD-rate reduction being 3.3% can be obtained.

AB - In H.265/HEVC, the random-access prediction structure helps to increase the coding efficiency and provides the temporal scalability. However, the quantization parameter cascading (QPC) strategy being used is not optimized in terms of the rate-distortion performance. This paper analyzes the rate and distortion dependency between temporal layers, and proposes a PSNR metric-based distortion model and a piecewise rate model to optimize the QPC. Experimental results demonstrate that the proposed algorithm achieves an average APSNR gain of 0.12dB with the maximum APSNR gain being 0.37dB. Meanwhile, an up to 8.7% BD-rate reduction with the average BD-rate reduction being 3.3% can be obtained.

KW - H.265/HEVC

KW - Quantization parameter cascading

KW - Random access prediction structure

KW - Rate and distortion dependency

KW - Rate-distortion optimization

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Yang Y, Wan S, Gong Y, Yang K. Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. IEEE Computer Society. 2016. p. 4235-4239. 7533158. (Proceedings - International Conference on Image Processing, ICIP). doi: 10.1109/ICIP.2016.7533158

Adaptive quantization parameter cascading for random-access prediction in H.265/HEVC based on dependent R-D models

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