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http://dx.doi.org/10.6109/jicce.2021.19.4.276

Noise Reduction for Photon Counting Imaging Using Discrete Wavelet Transform  

Lee, Jaehoon (Department of Computer Science and Networks, Kyushu Institute of Technology)
Kurosaki, Masayuki (Department of Computer Science and Networks, Kyushu Institute of Technology)
Cho, Myungjin (School of ICT, Robotics, and Mechanical Engineering, IITC, Hankyong National University)
Lee, Min-Chul (Department of Computer Science and Networks, Kyushu Institute of Technology)
Publication Information
Journal of information and communication convergence engineering / v.19, no.4, 2021 , pp. 276-283 More about this Journal
Abstract
In this paper, we propose an effective noise reduction method for photon counting imaging using a discrete wavelet transform. Conventional 2D photon counting imaging was used to visualize the object under dark conditions using statistical methods, such as the Poisson random process. The photons in the scene were estimated using a statistical method. However, photons which disturb the visualization and decrease the image quality may occur in the background where there is no object. Although median filters are used to reduce the noise, the noise in the scene remains. To remove the noise effectively, our proposed method uses the discrete wavelet transform, which removes the noise in the scene using a specific thresholding method that utilizes photon counting imaging characteristics. We conducted an optical experiment to demonstrate the denoising performance of the proposed method.
Keywords
Photon counting imaging; Statistical optics; Visualization; Image processing; Signal processing;
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