Abstract
Recently, various image quality assessment (IQA) metrics based on gradient similarity have been developed. In this paper, we extend the work of gradient magnitude similarity deviation (GMSD) and propose a more efficient metric. First, a novel similarity index is proposed, which gives the flexibility to tune the masking parameter to more closely match the human vision system (HVS). Then, we propose a multi-scale GMSD method by incorporating scores of luminance distortion at different scales. Furthermore, a method for measuring chromatic distortions in YIQ color space based on our metric is proposed. The final IQA index, MS-GMSDc, is obtained by combining luminance and chrominance scores. Experimental results on four comprehensive datasets clearly show that, compared with 14 state-of-the-art IQA methods, our method achieves the best performance for both grayscale and chromatic image assessment.
Original language | English |
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Title of host publication | 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1253-1257 |
Number of pages | 5 |
ISBN (Electronic) | 9781509041176 |
DOIs | |
Publication status | Published - 16 Jun 2017 |
Event | 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States Duration: 5 Mar 2017 → 9 Mar 2017 |
Other
Other | 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 |
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Country | United States |
City | New Orleans |
Period | 5/3/17 → 9/3/17 |
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Keywords
- Chromatic Distortion
- Gradient Magnitude Similarity
- Image Quality Assessment (IQA)
- Multi-scale
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
Cite this
Gradient magnitude similarity deviation on multiple scales for color image quality assessment. / Zhang, Bo; Sander, Pedro V.; Bermak, Amine.
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1253-1257 7952357.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Gradient magnitude similarity deviation on multiple scales for color image quality assessment
AU - Zhang, Bo
AU - Sander, Pedro V.
AU - Bermak, Amine
PY - 2017/6/16
Y1 - 2017/6/16
N2 - Recently, various image quality assessment (IQA) metrics based on gradient similarity have been developed. In this paper, we extend the work of gradient magnitude similarity deviation (GMSD) and propose a more efficient metric. First, a novel similarity index is proposed, which gives the flexibility to tune the masking parameter to more closely match the human vision system (HVS). Then, we propose a multi-scale GMSD method by incorporating scores of luminance distortion at different scales. Furthermore, a method for measuring chromatic distortions in YIQ color space based on our metric is proposed. The final IQA index, MS-GMSDc, is obtained by combining luminance and chrominance scores. Experimental results on four comprehensive datasets clearly show that, compared with 14 state-of-the-art IQA methods, our method achieves the best performance for both grayscale and chromatic image assessment.
AB - Recently, various image quality assessment (IQA) metrics based on gradient similarity have been developed. In this paper, we extend the work of gradient magnitude similarity deviation (GMSD) and propose a more efficient metric. First, a novel similarity index is proposed, which gives the flexibility to tune the masking parameter to more closely match the human vision system (HVS). Then, we propose a multi-scale GMSD method by incorporating scores of luminance distortion at different scales. Furthermore, a method for measuring chromatic distortions in YIQ color space based on our metric is proposed. The final IQA index, MS-GMSDc, is obtained by combining luminance and chrominance scores. Experimental results on four comprehensive datasets clearly show that, compared with 14 state-of-the-art IQA methods, our method achieves the best performance for both grayscale and chromatic image assessment.
KW - Chromatic Distortion
KW - Gradient Magnitude Similarity
KW - Image Quality Assessment (IQA)
KW - Multi-scale
UR - http://www.scopus.com/inward/record.url?scp=85023776221&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85023776221&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2017.7952357
DO - 10.1109/ICASSP.2017.7952357
M3 - Conference contribution
AN - SCOPUS:85023776221
SP - 1253
EP - 1257
BT - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -