REN, Hongdou, Shengmei ZHAO and Jozef GRUSKA. Edge detection based on single-pixel imaging. Optics Express. 2018, vol. 26, No 5, p. 5501-5511. ISSN 1094-4087. Available from: https://dx.doi.org/10.1364/OE.26.005501.
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Basic information
Original name Edge detection based on single-pixel imaging
Authors REN, Hongdou (156 China), Shengmei ZHAO (156 China) and Jozef GRUSKA (703 Slovakia, guarantor, belonging to the institution).
Edition Optics Express, 2018, 1094-4087.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher China
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.561
RIV identification code RIV/00216224:14330/18:00102587
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1364/OE.26.005501
UT WoS 000427147200037
Keywords in English Edge detection; Fourier transforms; Frequency domain analysis; Imaging systems; Pixels; Spectroscopy
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 5/11/2021 12:52.
Abstract
In the paper, we propose a new edge detection schemes, based on a single-pixel imaging in the frequency domain. In SCHEME-I, special sinusoidal patterns for the x-direction edge and also y-direction edge of the unknown object are first designed. The frequency spectrum for the edge is then obtained using the a four-step phase-shifting technique with the designed sinusoidal patterns in a single-pixel imaging system. In SCHEME-II, the frequency spectrum of the unknown object is first obtained, then the frequency spectrum for the edge is obtained by calculations. The resulting edges are finally obtained by the inverse Fourier transform on their frequency spectrum. We have also verified the proposed schemes by experiments and numerical simulations. The results show that the proposed schemes can produce higher quality edges of character and also image objects. Comparing with SCHEME-II, the application of SCHEME-I to high frequency components has greatly improved signal-to-noise ratio of the received data in the bucket detector, resulting in better experimental results. Comparing with the edge detection scheme by speckle-shifting in ghost imaging systems, the proposed SCHEME-I shows an improvement in the signal-to-noise ratio. Since a single-pixel imaging system is used, the proposed schemes are capable of reconstructing edges from indirect measurements. The number of measurements required can be e ectively reduced due to the sparsity of natural images in the Fourier domain and the conjugate symmetry of real-valued signals’ Fourier spectrum.
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