A random exploration based fast adaptive and selective mean filter for salt and pepper noise removal in satellite digital images
Abstract
The digital image is one of the discoveries that play an important role in various aspects of modern human life. These findings are useful in various fields, including defense (military and non-military), security, health, education, and others. In practice, the image acquisition process often suffers from problems, both in the process of capturing and transmitting images. Among the problems is the appearance of noise which results in the degradation of information in the image and thus disrupts further processes of image processing. One type of noise that damages digital images is salt and pepper noise which randomly changes the pixel values to 0 (black) or 255 (white). Researchers have proposed several methods to deal with this type of noise, including median filter, adaptive mean filter, switching median filter, modified decision based unsymmetric trimmed median filter, and different applied median filter. However, this method suffers from a decrease in performance when applied to images with high-intensity noise. Therefore, in this research, a new filtering method is proposed that can improve the image by randomly exploring pixels, then collecting the surrounding pixel data from the processed pixels (kernel). The kernel will be enlarged if there are no free-noise pixels in the kernel. Furthermore, the damaged pixels will be replaced using the mean data centering statistic. Images enhanced using the proposed method have better quality than the previous methods, both quantitatively (SSIM and PSNR) and qualitatively.
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Abdurrazzaq, A., Junoh, A. K., Wan Muhamad, W. Z. A., Yahya, Z., & Mohd, I. (2020). An overview of multi-filters for eliminating impulse noise for digital images. TELKOMNIKA (Telecommunication Computing Electronics and Control), 18(1), 385. https://doi.org/10.12928/telkomnika.v18i1.12888
ABDURRAZZAQ, A., MOHD, I., JUNOH, A. K., & YAHYA, Z. (2019). 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. (2019). 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
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
Chen, T., & Hong Ren Wu. (2001). Adaptive impulse detection using center-weighted median filters. IEEE Signal Processing Letters, 8(1), 1–3. https://doi.org/10.1109/97.889633
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
Ojha, A., & Tiwari, N. (2015). An image denoising technique using NAFSM with evolutionary algorithm. 2015 International Conference on Computational Intelligence and Communication Networks (CICN), 272–277. https://doi.org/10.1109/CICN.2015.61
[Online]. (n.d.). http://imageprocessingplace.com/rootles%20V3/image%20databases.TMF.
Sheik Fareed, S. B., & Khader, S. S. (2018). Fast adaptive and selective mean filter for the removal of high‐density salt and pepper noise. IET Image Processing, 12(8), 1378–1387. https://doi.org/10.1049/iet-ipr.2017.0199
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
Wenbin Luo. (2006). Efficient removal of impulse noise from digital images. IEEE Transactions on Consumer Electronics, 52(2), 523–527. https://doi.org/10.1109/TCE.2006.1649674
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.v5i3.14424
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