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Article

Automated Scattering Media Estimation in Peplography Using SVD and DCT

1
Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Iizuka 820-8502, Fukuoka, Japan
2
School of ICT, Robotics and Mechanical Engineering, IITC, Hankyong National University, Anseong 17579, Kyonggi-do, Republic of Korea
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Electronics 2025, 14(3), 545; https://doi.org/10.3390/electronics14030545
Submission received: 27 December 2024 / Revised: 17 January 2025 / Accepted: 27 January 2025 / Published: 29 January 2025
(This article belongs to the Special Issue Computational Imaging and Its Application)

Abstract

In this paper, we propose automation of estimating scattering media information in peplography using singular value decomposition (SVD) and discrete cosine transform (DCT). Conventional scattering media-removal methods reduce light scattering in images utilizing a variety of image-processing techniques and machine learning algorithms. However, under conditions of heavy scattering media, they may not clearly visualize the object information. Peplography has been proposed as a solution to this problem. Peplography is capable of visualizing the object information by estimating the scattering media information and detecting the ballistic photons from heavy scattering media. Following that, 3D information can be obtained by integral imaging. However, it is difficult to apply this method to real-world situations since the process of scattering media estimation in peplography is not automated. To overcome this problem, we use automatic scattering media-estimation methods using SVD and DCT. They can estimate the scattering media information automatically by truncating the singular value matrix and Gaussian low-pass filter in the frequency domain. To evaluate our proposed method, we implement the experiment with two different conditions and compare the result image with the conventional method using metrics such as structural similarity (SSIM), feature similarity (FSIMc), gradient magnitude similarity deviation (GMSD), and learned perceptual image path similarity (LPIPS).
Keywords: scattering media removal; three-dimensional imaging; digital image processing; singular value decomposition; discrete cosine transform scattering media removal; three-dimensional imaging; digital image processing; singular value decomposition; discrete cosine transform

Share and Cite

MDPI and ACS Style

Song, S.; Kim, H.-W.; Cho, M.; Lee, M.-C. Automated Scattering Media Estimation in Peplography Using SVD and DCT. Electronics 2025, 14, 545. https://doi.org/10.3390/electronics14030545

AMA Style

Song S, Kim H-W, Cho M, Lee M-C. Automated Scattering Media Estimation in Peplography Using SVD and DCT. Electronics. 2025; 14(3):545. https://doi.org/10.3390/electronics14030545

Chicago/Turabian Style

Song, Seungwoo, Hyun-Woo Kim, Myungjin Cho, and Min-Chul Lee. 2025. "Automated Scattering Media Estimation in Peplography Using SVD and DCT" Electronics 14, no. 3: 545. https://doi.org/10.3390/electronics14030545

APA Style

Song, S., Kim, H.-W., Cho, M., & Lee, M.-C. (2025). Automated Scattering Media Estimation in Peplography Using SVD and DCT. Electronics, 14(3), 545. https://doi.org/10.3390/electronics14030545

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