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http://dx.doi.org/10.6109/jkiice.2022.26.4.526

Fuzzy Logic Weight Filter for Salt and Pepper Noise Removal  

Lee, Hwa-Yeong (Dept. of Intelligent Robot Engineering, Pukyong National University)
Kim, Nam-Ho (School of Electrical Eng., Pukyong National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.26, no.4, 2022 , pp. 526-532 More about this Journal
Abstract
With the development of IoT technology, image processing is being utilized in various fields such as image analysis, image recognition, medical industry, and factory automation. Noise is generated in image data from causes such as defect in transmission line. Image noise must be removed because it damages the performance of the image processing application program. Salt and Pepper noise is a representative type of image noise, and various studies have been conducted to remove Salt and Pepper noise. Widely known methods include A-TMF, AFMF, and SDWF. However, as the noise density increases, the performance deteriorates. Thus, this paper proposes an algorithm that performs filtering using a fuzzy logic weight mask only in case of noise after noise determination. In order to prove the noise removal performance of the proposed algorithm, an experiment was performed on images with 10% to 90% noise added and the PSNR was compared.
Keywords
Image processing; Salt and Pepper; Fuzzy logic; Weight; PSNR;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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