Recursive trimmed filter in eliminating high density impulse noise from digital image
Abstract
Advances in technology have made it easier to share media over the Internet. In the process of media sharing, a media may receive noise or interference that results in loss of information. In this paper, a new method to remove Salt and Pepper noise from images based on recursive method will be presented. The first stage is to recognize the noise from the damaged image, the damaged pixels will be replaced by the mean of the surrounding window, the difference with other methods is the use of recursive approach that aims to minimize the size of the window in the recovery process.
Keywords
Full Text:
PDFReferences
Abdurrazzaq, A., Mohd, I., Junoh, A. K., & Yahya, Z. (2019a). A hybrid of tropical-singular value decomposition method for salt and peppernoise removal. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 27(3), 1667–1679. https://doi.org/10.3906/elk-1807-93
Abdurrazzaq, A., Mohd, I., Junoh, A. K., & Yahya, Z. (2019b). Modified tropical algebra based median filter for removing salt and pepper noise in digital image. IET Image Processing, 13(14), 2790–2795. https://doi.org/10.1049/iet-ipr.2018.6201
Abdurrazzaq, A., Mohd, I., Junoh, A. K., & Yahya, Z. (2020). Tropical algebra based adaptive filter for noise removal in digital image. Multimedia Tools and Applications, 79(27–28), 19659–19668. https://doi.org/10.1007/s11042-020-08847-0
Arias-Castro, E., & Donoho, D. L. (2009). Does median filtering truly preserve edges better than linear filtering? The Annals of Statistics, 37(3). https://doi.org/10.1214/08-AOS604
Chan, R. H., Chung-Wa, & Nikolova, M. (2005). Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization. IEEE Transactions on Image Processing, 14(10), 1479–1485. https://doi.org/10.1109/TIP.2005.852196
Charmouti, B., Junoh, A. K., Abdurrazzaq, A., & Mashor, M. Y. (2022). A new denoising method for removing salt & pepper noise from image. Multimedia Tools and Applications, 81(3), 3981–3993. https://doi.org/10.1007/s11042-021-11615-3
Erkan, U., Enginoglu, S., & Thanh, D. N. H. (2019). A Recursive Mean Filter for Image Denoising. 2019 International Artificial Intelligence and Data Processing Symposium (IDAP), 1–5. https://doi.org/10.1109/IDAP.2019.8875957
Erkan, U., Gökrem, L., & Enginoğlu, S. (2018). Different applied median filter in salt and pepper noise. Computers & Electrical Engineering, 70, 789–798. https://doi.org/10.1016/j.compeleceng.2018.01.019
Fan, H., Li, C., Guo, Y., Kuang, G., & Ma, J. (2018). Spatial–Spectral Total Variation Regularized Low-Rank Tensor Decomposition for Hyperspectral Image Denoising. IEEE Transactions on Geoscience and Remote Sensing, 56(10), 6196–6213. https://doi.org/10.1109/TGRS.2018.2833473
Faragallah, O. S., El-Hoseny, H., El-Shafai, W., El-Rahman, W. A., El-Sayed, H. S., El-Rabaie, E.-S. M., El-Samie, F. E. A., & Geweid, G. G. N. (2021). A Comprehensive Survey Analysis for Present Solutions of Medical Image Fusion and Future Directions. IEEE Access, 9, 11358–11371. https://doi.org/10.1109/ACCESS.2020.3048315
Giegerich, R., Meyer, C., & Steffen, P. (2004). A discipline of dynamic programming over sequence data. Science of Computer Programming, 51(3), 215–263. https://doi.org/10.1016/j.scico.2003.12.005
Goel, N., Kaur, H., & Saxena, J. (2020). Modified decision based unsymmetric adaptive neighborhood trimmed mean filter for removal of very high density salt and pepper noise. Multimedia Tools and Applications, 79(27–28), 19739–19768. https://doi.org/10.1007/s11042-020-08687-y
Huang, T., Yang, G., & Tang, G. (1979). A fast two-dimensional median filtering algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing, 27(1), 13–18. https://doi.org/10.1109/TASSP.1979.1163188
Image database. (n.d.). (n.d.). Https://Imageprocessingplace.Com/Rootles%20V3/Image%20databases.TMF.
Jayaraman, S., S, E., & Veerakumar, T. (2009). Digital image processing (1st edition). Tata McGraw-Hill Education.
Karthik, B., Krishna Kumar, T., Vijayaragavan, S. P., & Sriram, M. (2021). RETRACTED ARTICLE: Removal of high density salt and pepper noise in color image through modified cascaded filter. Journal of Ambient Intelligence and Humanized Computing, 12(3), 3901–3908. https://doi.org/10.1007/s12652-020-01737-1
Lin, H.-M., & Willson, A. N. (1988). Median filters with adaptive length. IEEE Transactions on Circuits and Systems, 35(6), 675–690. https://doi.org/10.1109/31.1805
Qin, F., Jiang, L., Xie, L., Cao, L., Zhu, L., Li, C., Zhang, Y., & Wen, X. (2022). An adaptive median filtering denoising algorithm for pepper and salt noised image. In D. Xu & L. Xiao (Eds.), Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021) (p. 123). SPIE. https://doi.org/10.1117/12.2623480
Rosin, P., & Collomosse, J. (2012). Image and video-based artistic stylization. Springer.
Singh, V., Dev, R., Dhar, N. K., Agrawal, P., & Verma, N. K. (2018). Adaptive Type-2 Fuzzy Approach for Filtering Salt and Pepper Noise in Grayscale Images. IEEE Transactions on Fuzzy Systems, 26(5), 3170–3176. https://doi.org/10.1109/TFUZZ.2018.2805289
Sun, T., & Neuvo, Y. (1994). Detail-preserving median based filters in image processing. Pattern Recognition Letters, 15(4), 341–347. https://doi.org/10.1016/0167-8655(94)90082-5
Toh, K. K. V., & Isa, N. A. M. (2010). Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction. IEEE Signal Processing Letters, 17(3), 281–284. https://doi.org/10.1109/LSP.2009.2038769
Wang, G., Li, D., Pan, W., & Zang, Z. (2010). Modified switching median filter for impulse noise removal. Signal Processing, 90(12), 3213–3218. https://doi.org/10.1016/j.sigpro.2010.05.026
Zhang, C., & Wang, K. (2015). A switching median–mean filter for removal of high-density impulse noise from digital images. Optik, 126(9–10), 956–961. https://doi.org/10.1016/j.ijleo.2015.02.085
Zhou Wang, & Zhang, D. (1999). Progressive switching median filter for the removal of impulse noise from highly corrupted images. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 46(1), 78–80. https://doi.org/10.1109/82.749102
DOI: http://dx.doi.org/10.24042/djm.v6i1.16382
Refbacks
- There are currently no refbacks.
Copyright (c) 2023 Desimal: Jurnal Matematika
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Desimal: Jurnal Matematika is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
