GEQM: A quality metric for gray-level edge maps based on structural matching

Won Dong Jang; Jae Young Sim; Chang-Su Kim

doi:10.1109/ICASSP.2014.6853580

GEQM: A quality metric for gray-level edge maps based on structural matching

Won Dong Jang, Jae Young Sim, Chang-Su Kim

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

Abstract

An accurate quality metric, called GEQM, for gray-level edge maps based on the structural matching of edge pixels is proposed in this work. We design the positional matching cost, which reflects the distance between two edge pixels, and the structural matching cost, which measures the structural shapes of edges as well as the differences of edge strength levels. Based on the cost functions, we perform the graph-cut optimization to obtain the optimal pixel-based matching between source and target edge maps bidirectionally. Finally, we compute the GEQM score by summing up the optimal matching costs of all edge pixels. Experimental results show that the proposed GEQM performs the edge map quality assessment more accurately and more reliably than conventional metrics. Especially, GEQM is suitable for assessing the qualities of synthesized intermediate views in multi-view image processing.

Original language	English
Title of host publication	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	171-174
Number of pages	4
ISBN (Print)	9781479928927
DOIs	https://doi.org/10.1109/ICASSP.2014.6853580
Publication status	Published - 2014 Jan 1
Event	2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy Duration: 2014 May 4 → 2014 May 9

Other

Other	2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Country/Territory	Italy
City	Florence
Period	14/5/4 → 14/5/9

ASJC Scopus subject areas

Signal Processing
Software
Electrical and Electronic Engineering

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10.1109/ICASSP.2014.6853580

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GEQM : A quality metric for gray-level edge maps based on structural matching. / Jang, Won Dong; Sim, Jae Young; Kim, Chang-Su.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 171-174 6853580.

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

Jang, WD, Sim, JY & Kim, C-S 2014, GEQM: A quality metric for gray-level edge maps based on structural matching. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings., 6853580, Institute of Electrical and Electronics Engineers Inc., pp. 171-174, 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence, Italy, 14/5/4. https://doi.org/10.1109/ICASSP.2014.6853580

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abstract = "An accurate quality metric, called GEQM, for gray-level edge maps based on the structural matching of edge pixels is proposed in this work. We design the positional matching cost, which reflects the distance between two edge pixels, and the structural matching cost, which measures the structural shapes of edges as well as the differences of edge strength levels. Based on the cost functions, we perform the graph-cut optimization to obtain the optimal pixel-based matching between source and target edge maps bidirectionally. Finally, we compute the GEQM score by summing up the optimal matching costs of all edge pixels. Experimental results show that the proposed GEQM performs the edge map quality assessment more accurately and more reliably than conventional metrics. Especially, GEQM is suitable for assessing the qualities of synthesized intermediate views in multi-view image processing.",

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N2 - An accurate quality metric, called GEQM, for gray-level edge maps based on the structural matching of edge pixels is proposed in this work. We design the positional matching cost, which reflects the distance between two edge pixels, and the structural matching cost, which measures the structural shapes of edges as well as the differences of edge strength levels. Based on the cost functions, we perform the graph-cut optimization to obtain the optimal pixel-based matching between source and target edge maps bidirectionally. Finally, we compute the GEQM score by summing up the optimal matching costs of all edge pixels. Experimental results show that the proposed GEQM performs the edge map quality assessment more accurately and more reliably than conventional metrics. Especially, GEQM is suitable for assessing the qualities of synthesized intermediate views in multi-view image processing.

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GEQM: A quality metric for gray-level edge maps based on structural matching

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