EN
TR
Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images
Abstract
This paper proposes a new Different Adaptive Modified Riesz Mean Filter (DAMRmF), for high-density salt-and-pepper noise (SPN) removal. DAMRmF operationalizes a pixel weight function and adaptivity condition of Adaptive Median Filter (AMF). In the simulation, the proposed filter is compared with Adaptive Frequency Median Filter (AFMF), Three-Values-Weighted Method (TVWM), Unbiased Weighted Mean Filter (UWMF), Different Applied Median Filter (DAMF), Adaptive Weighted Mean Filter (AWMF), Adaptive Cesáro Mean Filter (ACmF), Adaptive Riesz Mean Filter (ARmF), and Improved Adaptive Weighted Mean Filter (IAWMF) for 20 traditional test images with noise levels from 60% to 90%. The results show that DAMRmF outperforms the state-of-the-art filters in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) values. Moreover, DAMRmF also performs better than the state-of-the-art filters concerning mean PSNR and SSIM results. We finally discuss DAMRmF for further research
Keywords
References
- Enginoğlu, S., Erkan, U., & Memiş, S., (2019). Pixel similarity-based adaptive Riesz mean filter for salt-and-pepper noise removal, Multimedia Tools and Applications, 78(24), 35401–35418.
- Enginoğlu, S., Erkan, U., & Memiş, S., (2020). Adaptive Cesáro mean filter for salt-and-pepper noise removal, El-Cezeri Journal of Science and Engineering, 7(1), 304–314. Erkan, U., Enginoğlu, S., Thanh, D. N. H., & Hieu, L. M., (2020a). Adaptive frequency median filter for the salt-and-pepper denoising problem, IET Image Processing, 14(7), 1291–1302.
- Erkan, U., Gökrem, L., & Enginoğlu, S., (2018). Different applied median filter in salt and pepper noise, Computer and Electrical Engineering, 70, 789–798.
- Erkan, U., Thanh, D. N. H., Enginoğlu, S., & Memiş, S., (2020b). Improved adaptive weighted mean filter for salt-and-pepper noise removal, 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), Istanbul, Turkey, pp. 1–5.
- Gonzalez, R. C., & Woods, R. E., (2018). Digital image processing. New York: Pearson.
- Hausen, R., & Robertson, B. E., (2020). Morpheus: A deep learning framework for the pixel-level analysis of astronomical image data. The Astrophysical Journal Supplement Series, 248(20), 1–37.
- Hwang, H., & Haddad, R. A., (1995) Adaptive Median Filters: New Algorithms and Results. IEEE Transactions on Image Processing, 4(4), 499–502.
- Kandemir, C., Kalyoncu, C., & Toygar, Ö., (2015). A weighted mean filter with spatial-bias elimination for impulse noise removal, Digital Signal Processing, 46, 164–174.
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
April 30, 2021
Submission Date
February 2, 2021
Acceptance Date
April 4, 2021
Published in Issue
Year 2021 Number: 23
APA
Memiş, S., & Erkan, U. (2021). Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images. Avrupa Bilim Ve Teknoloji Dergisi, 23, 359-367. https://doi.org/10.31590/ejosat.873312
AMA
1.Memiş S, Erkan U. Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images. EJOSAT. 2021;(23):359-367. doi:10.31590/ejosat.873312
Chicago
Memiş, Samet, and Uğur Erkan. 2021. “Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images”. Avrupa Bilim Ve Teknoloji Dergisi, nos. 23: 359-67. https://doi.org/10.31590/ejosat.873312.
EndNote
Memiş S, Erkan U (April 1, 2021) Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images. Avrupa Bilim ve Teknoloji Dergisi 23 359–367.
IEEE
[1]S. Memiş and U. Erkan, “Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images”, EJOSAT, no. 23, pp. 359–367, Apr. 2021, doi: 10.31590/ejosat.873312.
ISNAD
Memiş, Samet - Erkan, Uğur. “Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images”. Avrupa Bilim ve Teknoloji Dergisi. 23 (April 1, 2021): 359-367. https://doi.org/10.31590/ejosat.873312.
JAMA
1.Memiş S, Erkan U. Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images. EJOSAT. 2021;:359–367.
MLA
Memiş, Samet, and Uğur Erkan. “Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images”. Avrupa Bilim Ve Teknoloji Dergisi, no. 23, Apr. 2021, pp. 359-67, doi:10.31590/ejosat.873312.
Vancouver
1.Samet Memiş, Uğur Erkan. Different Adaptive Modified Riesz Mean Filter For High-Density Salt-and-Pepper Noise Removal in Grayscale Images. EJOSAT. 2021 Apr. 1;(23):359-67. doi:10.31590/ejosat.873312
Cited By
A very fast and efficient multistage selective convolution filter for removal of salt and pepper noise
Journal of Ambient Intelligence and Humanized Computing
https://doi.org/10.1007/s12652-022-03747-7A new approach for SPN removal: nearest value based mean filter
PeerJ Computer Science
https://doi.org/10.7717/peerj-cs.1160CAMFv2: Better, faster and stronger for electrochemiluminescence image denoising
Applied Intelligence
https://doi.org/10.1007/s10489-025-06652-6Central tendency approach: A modified recursive filter for impulse noise removal in SAR and optical satellite images
Al-Jabar : Jurnal Pendidikan Matematika
https://doi.org/10.24042/ajpm.v16i1.24244CNN-assisted statistical prediction-error analysis for impulse noise removal in color images
Multimedia Tools and Applications
https://doi.org/10.1007/s11042-026-21518-w