Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation

Gaoxing Chen; Zhenyu Liu; Tetsunori Kobayashi; Takeshi Ikenaga

doi:10.1109/CISP-BMEI.2016.7852694

Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation

Gaoxing Chen, Zhenyu Liu, Tetsunori Kobayashi, Takeshi Ikenaga

Graduate School of Information, Production and Systems

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

1 Citation (Scopus)

Abstract

High efficiency video coding (HEVC) is the latest international video compression standard that achieves double compression efficiency than the previous standard H.264/AVC. To increase the compression accuracy, HEVC employs the coding unit (CU) ranging from 8 × 8 to 64 × 64. However, the encoding complexity of HEVC increase a lot since the manifold partition sizes. A lot of works are focused on reducing the complexity but didn't considered the feasibility of hardware implementation. This paper proposes a hardware friendly fast depth range definition algorithm based on multiple features. Block texture feature, quantization feature and block motion feature are utilized. Block texture feature is based on the texture similarity in consecutive frames. Quantization feature is based on the compression regularity of HEVC. Block motion feature is for compensate the difference caused by the moving object. Comparing with the original HEVC, the proposed method can saved about 33.72% of the processing time with 0.76% of BD-bitrate increase on average.

Original language	English
Title of host publication	Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	124-128
Number of pages	5
ISBN (Electronic)	9781509037100
DOIs	https://doi.org/10.1109/CISP-BMEI.2016.7852694
Publication status	Published - 2017 Feb 13
Event	9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016 - Datong, China Duration: 2016 Oct 15 → 2016 Oct 17

Other

Other	9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016
Country/Territory	China
City	Datong
Period	16/10/15 → 16/10/17

Keywords

block texture
depth decision
HEVC
inter prediction
quantization

ASJC Scopus subject areas

Biomedical Engineering
Signal Processing
Information Systems

Access to Document

10.1109/CISP-BMEI.2016.7852694

Cite this

Chen, G., Liu, Z., Kobayashi, T., & Ikenaga, T. (2017). Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation. In Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016 (pp. 124-128). Article 7852694 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISP-BMEI.2016.7852694

Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation. / Chen, Gaoxing; Liu, Zhenyu; Kobayashi, Tetsunori et al.
Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 124-128 7852694.

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

Chen, G, Liu, Z, Kobayashi, T & Ikenaga, T 2017, Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation. in Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016., 7852694, Institute of Electrical and Electronics Engineers Inc., pp. 124-128, 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016, Datong, China, 16/10/15. https://doi.org/10.1109/CISP-BMEI.2016.7852694

Chen G, Liu Z, Kobayashi T , Ikenaga T. Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation. In Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 124-128. 7852694 doi: 10.1109/CISP-BMEI.2016.7852694

@inproceedings{8c95f67b5a044fc49ceaf2a6217f2060,

title = "Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation",

abstract = "High efficiency video coding (HEVC) is the latest international video compression standard that achieves double compression efficiency than the previous standard H.264/AVC. To increase the compression accuracy, HEVC employs the coding unit (CU) ranging from 8 × 8 to 64 × 64. However, the encoding complexity of HEVC increase a lot since the manifold partition sizes. A lot of works are focused on reducing the complexity but didn't considered the feasibility of hardware implementation. This paper proposes a hardware friendly fast depth range definition algorithm based on multiple features. Block texture feature, quantization feature and block motion feature are utilized. Block texture feature is based on the texture similarity in consecutive frames. Quantization feature is based on the compression regularity of HEVC. Block motion feature is for compensate the difference caused by the moving object. Comparing with the original HEVC, the proposed method can saved about 33.72% of the processing time with 0.76% of BD-bitrate increase on average.",

keywords = "block texture, depth decision, HEVC, inter prediction, quantization",

author = "Gaoxing Chen and Zhenyu Liu and Tetsunori Kobayashi and Takeshi Ikenaga",

year = "2017",

month = feb,

day = "13",

doi = "10.1109/CISP-BMEI.2016.7852694",

language = "English",

pages = "124--128",

booktitle = "Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016 ; Conference date: 15-10-2016 Through 17-10-2016",

}

TY - GEN

T1 - Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation

AU - Chen, Gaoxing

AU - Liu, Zhenyu

AU - Kobayashi, Tetsunori

AU - Ikenaga, Takeshi

PY - 2017/2/13

Y1 - 2017/2/13

N2 - High efficiency video coding (HEVC) is the latest international video compression standard that achieves double compression efficiency than the previous standard H.264/AVC. To increase the compression accuracy, HEVC employs the coding unit (CU) ranging from 8 × 8 to 64 × 64. However, the encoding complexity of HEVC increase a lot since the manifold partition sizes. A lot of works are focused on reducing the complexity but didn't considered the feasibility of hardware implementation. This paper proposes a hardware friendly fast depth range definition algorithm based on multiple features. Block texture feature, quantization feature and block motion feature are utilized. Block texture feature is based on the texture similarity in consecutive frames. Quantization feature is based on the compression regularity of HEVC. Block motion feature is for compensate the difference caused by the moving object. Comparing with the original HEVC, the proposed method can saved about 33.72% of the processing time with 0.76% of BD-bitrate increase on average.

AB - High efficiency video coding (HEVC) is the latest international video compression standard that achieves double compression efficiency than the previous standard H.264/AVC. To increase the compression accuracy, HEVC employs the coding unit (CU) ranging from 8 × 8 to 64 × 64. However, the encoding complexity of HEVC increase a lot since the manifold partition sizes. A lot of works are focused on reducing the complexity but didn't considered the feasibility of hardware implementation. This paper proposes a hardware friendly fast depth range definition algorithm based on multiple features. Block texture feature, quantization feature and block motion feature are utilized. Block texture feature is based on the texture similarity in consecutive frames. Quantization feature is based on the compression regularity of HEVC. Block motion feature is for compensate the difference caused by the moving object. Comparing with the original HEVC, the proposed method can saved about 33.72% of the processing time with 0.76% of BD-bitrate increase on average.

KW - block texture

KW - depth decision

KW - HEVC

KW - inter prediction

KW - quantization

UR - http://www.scopus.com/inward/record.url?scp=85016026519&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85016026519&partnerID=8YFLogxK

U2 - 10.1109/CISP-BMEI.2016.7852694

DO - 10.1109/CISP-BMEI.2016.7852694

M3 - Conference contribution

AN - SCOPUS:85016026519

SP - 124

EP - 128

BT - Proceedings - 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2016

Y2 - 15 October 2016 through 17 October 2016

ER -

Multi-feature based fast depth decision in HEVC inter prediction for VLSI implementation

Abstract

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this