A Sequential Median-Gaussian Cascade for Enhanced Suppression of Salt-and-Pepper Noise in Digital Images
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Salt-and-Pepper Noise, Cascade Image Filtering, Spatial Coherence, Order-Statistic Filters, Hybrid Median-Gaussian Denoising
Abstract
Salt and pepper noise remains a major contributor to the degradation of digital imaging system and has negative impact on the visual quality of images and the performance of the computer vision pipeline. Classical spatial filtering methods provide some sort of remedy but both methods have their own disadvantages; linear filters can blur prominent features, and nonlinear median-based filters can also produce block artifacts. The current research conducts a systematic exploration of cascading median-Gaussian filtering of removing impulse noise. Under this arrangement, the median filter step is useful in removing the outlier, and the later Gaussian convolution replenishes the coherence in terms of structure. A large amount of experimentation on standardized test images with noise densities of 1 to 10 percent, shows that the cascade is always outperforming the standalone mean filter, median filter, and Gaussian filter, especially in moderate-high noise conditions. There is statistically significant quantitative performance improvement, measured in Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The suggested approach shows computational efficiency, easy implement ability, and is well adapted to the integration into real-time or resource-constrained imaging systems, where interpretability and reliability are the primary factors of concern.
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References
[1] R. C. Gonzalez and R. E. Woods, Digital Image Processing. New York, NY, USA: Pearson, 2018.
[2] A. K. Jain, Fundamentals of Digital Image Processing. Englewood Cliffs, NJ, USA: Prentice Hall, 1989.
[3] J. W. Tukey, Exploratory Data Analysis. Reading, MA, USA: Addison-Wesley, 1977.
[4] H. Hwang and R. A. Haddad, "Adaptive median filters: New algorithms and results," IEEE Transactions on Image Processing, vol. 4, no. 4, pp. 499–502, 1995.
[5] S. Esakkirajan, T. Veerakumar, A. N. Subramanyam, and C. H. PremChand, "Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter," IEEE Signal Processing Letters, vol. 18, no. 5, pp. 287–290, 2011.
[6] F. Ullah et al., "A new hybrid image denoising algorithm using adaptive median filter and modified decision-based median filter," Scientific Reports, vol. 15, p. 9228, 2025.
[7] W. K. Pratt, Digital Image Processing. Hoboken, NJ, USA: Wiley Interscience, 2007.
[8] T. Chen, K.-K. Ma, and L.-H. Chen, "Tri-state median filter for image denoising," IEEE Transactions on Image Processing, vol. 8, no. 12, pp. 1834–1838, 1999.
[9] K. S. Srinivasan and D. Ebenezer, "A new fast and efficient decision-based algorithm for removal of high-density impulse noises," IEEE Signal Processing Letters, vol. 14, no. 3, pp. 189–192, 2007.
[10] L. G. Shapiro and G. C. Stockman, Computer Vision. Upper Saddle River, NJ, USA: Prentice Hall, 2001.
[11] K. Zhang, W. Zuo, Y. Chen, D. Meng, and L. Zhang, "Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising," IEEE Transactions on Image Processing, vol. 26, no. 7, pp. 3142–3155, 2017.
[12] R. Dash et al., "Deep Learning based Image Denoising," Archives of Computational Methods in Engineering, 2024.
[13] D. Zosso, J. An, and G. Steidl, "Adaptive Total Variation Denoising Based on Noise Estimation," SIAM Journal on Imaging Sciences, vol. 10, no. 3, pp. 1220–1260, 2017.
[14] M. Lebrun, A. Buades, and J. M. Morel, "A Nonlocal Bayesian Image Denoising Algorithm," SIAM Journal on Imaging Sciences, vol. 6, no. 3, pp. 1665–1688, 2013.
[15] Z. Anwar et al., "Modern techniques for impulse noise removal: A review," Journal of King Saud University - Computer and Information Sciences, 2023.
[16] A. Osman, “3D modelling using partial differential equations (PDEs),” SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University), Jan. 2014, doi: https://doi.org/10.13140/rg.2.2.28026.75204.
[17] Beitalmal, Abdusslam. "Efficient 3D Surface Patch Compression and Reconstruction Using Parametric Descriptions and Transform Techniques." Journal of Pure & Applied Sciences 22, no. 1 (2023): 107-116, doi: https://doi.org/10.51984/jopas.v22i1.2164.
[18] Beitalmal, Abdusslam Osman. "A Hybrid Physics-Informed Neural Network (PINN) And Finite Element Method (FEM) Framework for Multiscale Fluid-Structure Interaction Problems." RA Journal of Applied Research 11, no. 04 (2025).
[19] Beitalmal, Abdusslam Osman. "Optimizing Ecological Insights: A Comparative Study of Analytical and Numerical Approaches for Time-Fractional Fisher-KPP Equations." Libyan International Journal of Natural Sciences 2, no. 1 (2026): 1-9.
[20] Safaa Alhodairy and Abdusslam Beitalmal, “The Applications of Fourier Series Harmonics in Musical Tones,” Journal of Pure & Applied Sciences, vol. 23, no. 2, pp. 154–161, Nov. 2024, doi: https://doi.org/10.51984/jopas.v23i2.3590.
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