TY - GEN
T1 - Multi-focus Image Performance Evaluation Method Based on the Extraction and Combination of Multiple Metrics
AU - Li, Weitong
AU - Cheng, Yu
AU - Sun, Yuehui
AU - Xu, Shaoqiu
N1 - Funding Information:
The authors would like to thank the editor and the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. This work was supported by the National Science Foundation of China (Grant No.61471130), the Science and Technology Planning Projection of Guangdong Province, China (Grant No.2016B090918060, 2017A010101016) and Science and Technology Planning Project of Guangzhou City, China (Grand No.201604016079).
Publisher Copyright:
© 2017 IEEE.
PY - 2018/2/8
Y1 - 2018/2/8
N2 - In multi-focus image fusion, some objective metrics were proposed to evaluate the fused images and compare the corresponding fusion algorithms further. For an image, some metrics can acquire satisfied results, while others can't give credible conclusions. Single objective metric can't assess an image correctly and comprehensively, so multiple metrics may be combined to evaluate the fused images. In this paper, a method named multiple metrics extraction and combination is studied. First, a total set with some popularly cited and representative metrics is formed. Second, for each group of images, the appropriate metrics are extracted from the total set to construct an evaluation set. Therefore two sets of images may have diverse evaluation sets. Third, for each image of the same group, the extracted metrics are combined into three scalars with three measurement methods respectively. Finally, the consistency of measurement results is verified with the scalars. The simulations show that our method outperforms single metric and provides a new way to the research of performance evaluation.
AB - In multi-focus image fusion, some objective metrics were proposed to evaluate the fused images and compare the corresponding fusion algorithms further. For an image, some metrics can acquire satisfied results, while others can't give credible conclusions. Single objective metric can't assess an image correctly and comprehensively, so multiple metrics may be combined to evaluate the fused images. In this paper, a method named multiple metrics extraction and combination is studied. First, a total set with some popularly cited and representative metrics is formed. Second, for each group of images, the appropriate metrics are extracted from the total set to construct an evaluation set. Therefore two sets of images may have diverse evaluation sets. Third, for each image of the same group, the extracted metrics are combined into three scalars with three measurement methods respectively. Finally, the consistency of measurement results is verified with the scalars. The simulations show that our method outperforms single metric and provides a new way to the research of performance evaluation.
KW - image fusion
KW - metric extraction
KW - Multi-focus image
KW - performance evaluation
UR - https://www.scopus.com/pages/publications/85046697548
U2 - 10.1109/CIS.2017.00036
DO - 10.1109/CIS.2017.00036
M3 - Conference contribution
AN - SCOPUS:85046697548
T3 - Proceedings - 13th International Conference on Computational Intelligence and Security, CIS 2017
SP - 130
EP - 134
BT - Proceedings - 13th International Conference on Computational Intelligence and Security, CIS 2017
T2 - 13th International Conference on Computational Intelligence and Security, CIS 2017
Y2 - 15 December 2017 through 18 December 2017
ER -