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http://dx.doi.org/10.23087/jkicsp.2022.23.1.007

Weighted Filter Algorithm based on Distribution Pattern of Pixel Value for AWGN Removal  

Cheon, Bong-Won (Dept. of Intelligent Robot Eng., Pukyong National University)
Kim, Nam-Ho (School of Electrical Eng., Pukyong National University)
Publication Information
Journal of the Institute of Convergence Signal Processing / v.23, no.1, 2022 , pp. 44-49 More about this Journal
Abstract
Abstract Recently, with the development of IoT technology and communication media, various video equipment is being used in industrial fields. Image data acquired from cameras and sensors are easily affected by noise during transmission and reception, and noise removal is essential as it greatly affects system reliability. In this paper, we propose a weight filter algorithm based on the pixel value distribution pattern to preserve details in the process of restoring images damaged in AWGN. The proposed algorithm calculates weights according to the pixel value distribution pattern of the image and restores the image by applying a filtering mask. In order to analyze the noise removal performance of the proposed algorithm, it was simulated using enlarged image and PSNR compared to the existing method. The proposed algorithm preserves important characteristics of the image and shows the performance of efficiently removing noise compared to the existing method.
Keywords
AWGN; Weighted filter; Pixel value; Distribution pattern; PSNR;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 D. Chowdhury, S. K. Das, S. Nandy, A. Chakraborty, R. Goswami, and A. Chakraborty, "An Atomic Technique for Removal of Gaussian Noise from a Noisy Gray Scale Image using Low-Pass Convoluted Gaussian Filter," in 2019 International Conference on Opto-Electronics and Applied Optics (Optronix), Kolkata : India, pp. 1-6, 2019.
2 P. S. V. S. Sridhar, R. Caytiles, "Efficient Cloud Data Hosting Availability," Asia-pacific Journal of Convergent Research Interchange, HSST, ISSN : 2508-9080, vol. 3, no. 2, pp. 11-19, Jun. 2017. http://dx.doi.org/10.21742/APJCRI.2017.06.02.   DOI
3 K. Kai, L. Tingting, X. Xianchun, Z. Guoquan, and Z. Jianxin, "Study of Infrared Image Denoising Algorithm based on Steering Kernel Regression Image Guided Filter," in 2019 18th International Conference on Optical Communications and Networks (ICOCN), Huangshan : China, pp. 1-3, 2019.
4 B. W. Cheon, N. H. Kim, "Modified Gaussian Filter Algorithm using Quadtree Segmentation in AWGN Environment," Journal of the Korea Institute of Information and Communication Engineering, vol. 25, no. 9, pp. 1176-1182, Sept. 2021. DOI: 10.6109/jkiice.2021.25.9.1176.   DOI
5 X. Long, and N. H. Kim, "A Study on the Spatial Weighted Filter in AWGN Environment," Journal of the Korea Institute of Information and Communication Engineering, vol. 17, no. 3, pp. 724-729, Mar. 2013.   DOI
6 D. H. Shin, R. H. Park, S. J. Yang, and J. H. Jung, "Block-based Noise Estimation using Adaptive Gaussian Filtering," in 2005 Digest of Technical Papers. International Conference on Consumer Electronics, Las Vegas : USA, 2005, pp. 263-264.
7 S. I. Kwon, and N. H. Kim, "A Study on Composite Filter using Edge Information of Local Mask in AWGN Environments," Journal of the Korea Institute of Convergence Signal Processing, vol. 17, no. 2, pp. 71~76, Dec. 2016.   DOI