Modulation transfer function (MTF) measurement method based on support vector machine (SVM)

Zheng Zhang; Yueting Chen; Huajun Feng; Zhihai Xu; Qi Li

doi:10.1117/12.2266630

8 March 2017 Modulation transfer function (MTF) measurement method based on support vector machine (SVM)

Zheng Zhang, Yueting Chen, Huajun Feng, Zhihai Xu, Qi Li

Proceedings Volume 10255, Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016; 1025535 (2017) https://doi.org/10.1117/12.2266630
Event: Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016, 2016, Jinhua, Suzhou, Chengdu, Xi'an, Wuxi, China

Abstract

An imaging system’s spatial quality can be expressed by the system’s modulation spread function (MTF) as a function of spatial frequency in terms of the linear response theory. Methods have been proposed to assess the MTF of an imaging system using point, slit or edge techniques. The edge method is widely used for the low requirement of targets. However, the traditional edge methods are limited by the edge angle. Besides, image noise will impair the measurement accuracy, making the measurement result unstable. In this paper, a novel measurement method based on the support vector machine (SVM) is proposed. Image patches with different edge angles and MTF levels are generated as the training set. Parameters related with MTF and image structure are extracted from the edge images. Trained with image parameters and the corresponding MTF, the SVM classifier can assess the MTF of any edge image. The result shows that the proposed method has an excellent performance on measuring accuracy and stability.

Citation Download Citation

Zheng Zhang, Yueting Chen, Huajun Feng, Zhihai Xu, and Qi Li "Modulation transfer function (MTF) measurement method based on support vector machine (SVM)", Proc. SPIE 10255, Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016, 1025535 (8 March 2017); https://doi.org/10.1117/12.2266630

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