Phase Congruency based edge saliency detection and rate control for perceptual image and video coding

Gao Wei; Kwong Sam

doi:10.1109/SMC.2016.7844252

Phase Congruency based edge saliency detection and rate control for perceptual image and video coding

Gao Wei
, Kwong Sam

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

7 Citations (Scopus)

Abstract

Phase Congruency (PC) features are firstly introduced into image and video coding field in this paper. As an effective tool to measure the edge information for image textures, PC change can be used to evaluate the compression loss, i.e. the coding distortions in image and video coding. Firstly, the compression influences on PC maps are given and analyzed. Secondly, the relationship between the consumed bits and the PC distortion are modeled. Lastly, the Mean-Squared-Error (MSE) based and PC distortion based optimized Coding Tree Unit (CTU) level bit allocation solutions are combined as a two step bit allocation and rate control method for intra frames for High Efficiency Video Coding (HEVC). Experimental results demonstrate that, compared with the state-of-the-art JCTVC-K0103 and JCTVC-M0257 methods, for small size videos, the proposed method can achieve significant R-D performance gains, and also works well on PC map preservation, quality smoothness and bit rate accuracy.

Original language	English
Title of host publication	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Publisher	IEEE
Pages	264-269
ISBN (Print)	9781509018970
DOIs	https://doi.org/10.1109/SMC.2016.7844252
Publication status	Published - 6 Feb 2017
Event	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary Duration: 9 Oct 2016 → 12 Oct 2016

Conference

Conference	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Place	Hungary
City	Budapest
Period	9/10/16 → 12/10/16

Research Keywords

Bit allocation
Coding distortion metric
Edge detection
Edge saliency detection
High Efficiency Video Coding (HEVC)
Intra frame coding
Perceptual image and video coding
Phase Congruency (PC)
Rate control
Rate distortion modeling
Video coding

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10.1109/SMC.2016.7844252

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@inproceedings{b93b857b6d4e4f5290f97fa984458978,

title = "Phase Congruency based edge saliency detection and rate control for perceptual image and video coding",

abstract = "Phase Congruency (PC) features are firstly introduced into image and video coding field in this paper. As an effective tool to measure the edge information for image textures, PC change can be used to evaluate the compression loss, i.e. the coding distortions in image and video coding. Firstly, the compression influences on PC maps are given and analyzed. Secondly, the relationship between the consumed bits and the PC distortion are modeled. Lastly, the Mean-Squared-Error (MSE) based and PC distortion based optimized Coding Tree Unit (CTU) level bit allocation solutions are combined as a two step bit allocation and rate control method for intra frames for High Efficiency Video Coding (HEVC). Experimental results demonstrate that, compared with the state-of-the-art JCTVC-K0103 and JCTVC-M0257 methods, for small size videos, the proposed method can achieve significant R-D performance gains, and also works well on PC map preservation, quality smoothness and bit rate accuracy.",

keywords = "Bit allocation, Coding distortion metric, Edge detection, Edge saliency detection, High Efficiency Video Coding (HEVC), Intra frame coding, Perceptual image and video coding, Phase Congruency (PC), Rate control, Rate distortion modeling, Video coding",

author = "Gao Wei and Kwong Sam",

year = "2017",

month = feb,

day = "6",

doi = "10.1109/SMC.2016.7844252",

language = "English",

isbn = "9781509018970",

pages = "264--269",

booktitle = "2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings",

publisher = "IEEE",

address = "United States",

note = "2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 ; Conference date: 09-10-2016 Through 12-10-2016",

}

Wei, G & Sam, K 2017, Phase Congruency based edge saliency detection and rate control for perceptual image and video coding. in 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings., 7844252, IEEE, pp. 264-269, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, 9/10/16. https://doi.org/10.1109/SMC.2016.7844252

Phase Congruency based edge saliency detection and rate control for perceptual image and video coding. / Wei, Gao; Sam, Kwong.
2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. IEEE, 2017. p. 264-269 7844252.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Phase Congruency based edge saliency detection and rate control for perceptual image and video coding

AU - Wei, Gao

AU - Sam, Kwong

PY - 2017/2/6

Y1 - 2017/2/6

N2 - Phase Congruency (PC) features are firstly introduced into image and video coding field in this paper. As an effective tool to measure the edge information for image textures, PC change can be used to evaluate the compression loss, i.e. the coding distortions in image and video coding. Firstly, the compression influences on PC maps are given and analyzed. Secondly, the relationship between the consumed bits and the PC distortion are modeled. Lastly, the Mean-Squared-Error (MSE) based and PC distortion based optimized Coding Tree Unit (CTU) level bit allocation solutions are combined as a two step bit allocation and rate control method for intra frames for High Efficiency Video Coding (HEVC). Experimental results demonstrate that, compared with the state-of-the-art JCTVC-K0103 and JCTVC-M0257 methods, for small size videos, the proposed method can achieve significant R-D performance gains, and also works well on PC map preservation, quality smoothness and bit rate accuracy.

AB - Phase Congruency (PC) features are firstly introduced into image and video coding field in this paper. As an effective tool to measure the edge information for image textures, PC change can be used to evaluate the compression loss, i.e. the coding distortions in image and video coding. Firstly, the compression influences on PC maps are given and analyzed. Secondly, the relationship between the consumed bits and the PC distortion are modeled. Lastly, the Mean-Squared-Error (MSE) based and PC distortion based optimized Coding Tree Unit (CTU) level bit allocation solutions are combined as a two step bit allocation and rate control method for intra frames for High Efficiency Video Coding (HEVC). Experimental results demonstrate that, compared with the state-of-the-art JCTVC-K0103 and JCTVC-M0257 methods, for small size videos, the proposed method can achieve significant R-D performance gains, and also works well on PC map preservation, quality smoothness and bit rate accuracy.

KW - Bit allocation

KW - Coding distortion metric

KW - Edge detection

KW - Edge saliency detection

KW - High Efficiency Video Coding (HEVC)

KW - Intra frame coding

KW - Perceptual image and video coding

KW - Phase Congruency (PC)

KW - Rate control

KW - Rate distortion modeling

KW - Video coding

UR - https://www.scopus.com/pages/publications/85015722037

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85015722037&origin=recordpage

U2 - 10.1109/SMC.2016.7844252

DO - 10.1109/SMC.2016.7844252

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781509018970

SP - 264

EP - 269

BT - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

PB - IEEE

T2 - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016

Y2 - 9 October 2016 through 12 October 2016

ER -

Phase Congruency based edge saliency detection and rate control for perceptual image and video coding

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Research Keywords

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