Edge detection based on adaptive threshold b-spline wavelet for optical sub-aperture measuring

Shiqi Zhang; Mei Hui; Ming Liu; Zhu Zhao; Liquan Dong; Xiaohua Liu; Yuejin Zhao

doi:10.1117/12.2197122

7 August 2015 Edge detection based on adaptive threshold b-spline wavelet for optical sub-aperture measuring

Shiqi Zhang, Mei Hui, Ming Liu, Zhu Zhao, Liquan Dong, Xiaohua Liu, Yuejin Zhao

Proceedings Volume 9623, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems; 96230D (2015) https://doi.org/10.1117/12.2197122
Event: International Conference on Optical Instruments and Technology 2015, 2015, Beijing, China

Abstract

In the research of optical synthetic aperture imaging system, phase congruency is the main problem and it is necessary to detect sub-aperture phase. The edge of the sub-aperture system is more complex than that in the traditional optical imaging system. And with the existence of steep slope for large-aperture optical component, interference fringe may be quite dense when interference imaging. Deep phase gradient may cause a loss of phase information. Therefore, it’s urgent to search for an efficient edge detection method. Wavelet analysis as a powerful tool is widely used in the fields of image processing. Based on its properties of multi-scale transform, edge region is detected with high precision in small scale. Longing with the increase of scale, noise is reduced in contrary. So it has a certain suppression effect on noise. Otherwise, adaptive threshold method which sets different thresholds in various regions can detect edge points from noise. Firstly, fringe pattern is obtained and cubic b-spline wavelet is adopted as the smoothing function. After the multi-scale wavelet decomposition of the whole image, we figure out the local modulus maxima in gradient directions. However, it also contains noise, and thus adaptive threshold method is used to select the modulus maxima. The point which greater than threshold value is boundary point. Finally, we use corrosion and expansion deal with the resulting image to get the consecutive boundary of image.

Citation Download Citation

Shiqi Zhang, Mei Hui, Ming Liu, Zhu Zhao, Liquan Dong, Xiaohua Liu, and Yuejin Zhao "Edge detection based on adaptive threshold b-spline wavelet for optical sub-aperture measuring", Proc. SPIE 9623, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 96230D (7 August 2015); https://doi.org/10.1117/12.2197122

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KEYWORDS

Edge detection

Wavelets

Image filtering

Imaging systems

Wavelet transforms

Image processing

Mirrors

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