Direct Noise-Resistant Edge Detection with Edge-Sensitive Single-Pixel Imaging Modulation

Author:

Ma Mengchao1,Liang Wenbo1,Zhong Xiang1,Deng Huaxia2,Shi Dongfeng34ORCID,Wang Yingjian34,Xia Min5

Affiliation:

1. Anhui Province Key Laboratory of Measuring Theory and Precision Instruments, School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology, Hefei, Anhui 230009, China.

2. CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Modern Mechanics, University of Science and Technology of China, Hefei, Anhui 230027, China.

3. Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.

4. Advanced Laser Technology Laboratory of Anhui Province, Hefei 230037, China.

5. Department of Mechanical and Materials Engineering, University of Western Ontario, London, Ontario, Canada N6A 5B9.

Abstract

The majority of edge detection methods are applied after the capture of object photos. Thus, edge detection quality suffers when disturbances occur during imaging. This work proposes an effective edge detection technique for single-pixel imaging (SI). A sequence of edge-sensitive single-pixel imaging (ESI) and single-round edge-sensitive single-pixel imaging (SESI) modulation patterns is specially designed to extract the edges of unknown objects directly without the need for any previous images. The modulation patterns are formed by convolving the SI basis patterns with a second-order differential operator. Compared with existing published edge detection methods, experimental results revealed that the proposed SESI increased the signal-to-noise ratio by at least 228%, thereby reducing the edge detection time by at least half. The edge detection performance of the SESI scheme was also demonstrated on moving objects, with SESI detecting clear edges even when the target was in motion. Moreover, unlike traditional methods, ESI and SESI are immune to light interference and can detect clear edges of objects even if the objects are corrupted by severe interference from laser or light-emitting diode light sources, whereas traditional methods exhibit substantial noise contamination. Consequently, ESI and SESI can lay the groundwork for fast and robust edge detection operations without imaging.

Publisher

American Association for the Advancement of Science (AAAS)

Reference41 articles.

1. A computational approach to edge detection;Canny J;IEEE Trans Pattern Anal Mach Intell,1986

2. Theory of edge detection;Marr D;Proc R Soc Lond B Biol Sci,1980

3. On edge detection;Torre V;IEEE Trans Pattern Anal Mach Intell,1986

4. Richer convolutional features for edge detection;Liu Y;IEEE Trans Pattern Anal Mach Intell,2019

5. BDCN: Bi-directional cascade network for perceptual edge detection;He J;IEEE Trans Pattern Anal Mach Intell,2022

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