Removal of Multiplicative Gamma Noise from Images via SRAD Model Amelioration
Received: 30 September 2021 | Revised: 26 October 2021 and 1 November 2021 | Accepted: 8 November 2021 | Online: 11 December 2021
In this paper, an improved Speckle Reducing Anisotropic Diffusion (SRAD), destined to remove multiplicative gamma noise applied to different images is proposed. The basic idea is to divide the image into several riddled areas and then calculate the Equivalent Number of Look (ENL) of each region. The largest value of the ENL is the best optimal homogeneous region of the image. This optimal choice allows us to solve the major problem of the SRAD algorithm articulated around a visual choice of the homogeneous region which is not satisfactory and causes non-uniformity in this area. To give more validity to the proposed method, several experimentations were conducted using different kinds of images and were approved by some quantitative metrics like PSNR, SNR, VSNR, and SSIM. The computer simulation results confirm the efficiency of the proposed method which outperformances the classical SRAD method.
Keywords:multiplicative gamma noise, SRAD, ENL, optimal homogeneous zone, speckle noise
Y. Yu and S. T. Acton, "Speckle reducing anisotropic diffusion," IEEE Transactions on Image Processing, vol. 11, no. 11, pp. 1260–1270, Nov. 2002, https://doi.org/10.1109/TIP.2002.804276.
S. N. Anfinsen, A. P. Doulgeris, and T. Eltoft, "Estimation of the Equivalent Number of Looks in Polarimetric Synthetic Aperture Radar Imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 11, pp. 3795–3809, Nov. 2009, https://doi.org/10.1109/TGRS.2009.2019269.
K. Kim, S. Jung, and J.-H. Kim, "Adaptive speckle filtering for real-time computing in low earth orbit satellite synthetic aperture radar," ICT Express, vol. 7, no. 2, pp. 187–190, Jun. 2021, https://doi.org/10.1016/j.icte.2021.02.003.
D. K. Nirmala, "A Brief Study on the Various Noise Models in Digital Image Processing," International Journal of Emerging Technologies in Engineering Research, vol. 5, no. 10, pp. 17–23, Oct. 2017.
N. Diffellah, Z. E. Baarir, F. Derraz, and A. Taleb-Ahmed, "A Global Variational Filter for Restoring Noised Images with Gamma Multiplicative Noise," Engineering, Technology & Applied Science Research, vol. 9, no. 3, pp. 4188–4195, Jun. 2019, https://doi.org/10.48084/etasr.2737.
A. Horé and D. Ziou, "Image Quality Metrics: PSNR vs. SSIM," in 2010 20th International Conference on Pattern Recognition, Istanbul, Turkey, Aug. 2010, pp. 2366–2369, https://doi.org/10.1109/ICPR.2010.579.
M. V. Sarode and P. R. Deshmukh, "Image Sequence Denoising with Motion Estimation in Color Image Sequences," Engineering, Technology & Applied Science Research, vol. 1, no. 6, pp. 139–143, Dec. 2011, https://doi.org/10.48084/etasr.54.
H. T. R. Kurmasha, A. F. H. Alharan, C. S. Der, and N. H. Azami, "Enhancement of Edge-based Image Quality Measures Using Entropy for Histogram Equalization-based Contrast Enhancement Techniques," Engineering, Technology & Applied Science Research, vol. 7, no. 6, pp. 2277–2281, Dec. 2017, https://doi.org/10.48084/etasr.1625.
C. Plapous, C. Marro, and P. Scalart, "Improved Signal-to-Noise Ratio Estimation for Speech Enhancement," IEEE Transactions on Audio, Speech, and Language Processing, vol. 14, no. 6, pp. 2098–2108, Nov. 2006, https://doi.org/10.1109/TASL.2006.872621.
D. M. Chandler and S. S. Hemami, "VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images," IEEE Transactions on Image Processing, vol. 16, no. 9, pp. 2284–2298, Sep. 2007, https://doi.org/10.1109/TIP.2007.901820.
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: from error visibility to structural similarity," IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, Apr. 2004, https://doi.org/10.1109/TIP.2003.819861.
A. Siddig, Z. Guo, Z. Zhou, and B. Wu, "An image denoising model based on a fourth-order nonlinear partial differential equation," Computers & Mathematics with Applications, vol. 76, no. 5, pp. 1056–1074, Sep. 2018, https://doi.org/10.1016/j.camwa.2018.05.040.
R. Chan, H. Yang, and T. Zeng, "A Two-Stage Image Segmentation Method for Blurry Images with Poisson or Multiplicative Gamma Noise," SIAM Journal on Imaging Sciences, vol. 7, no. 1, pp. 98–127, Jan. 2014, https://doi.org/10.1137/130920241.
K. Dooley, Image union. 2017.
"Attribution 2.0 Generic — CC BY 2.0," Creative Commons. https://creativecommons.org/licenses/by/2.0/ (accessed Nov. 16, 2021).
NASA Goddard Space Flight Center, First NAC Image Obtained in Mercury Orbit. 2011.
"Transportation airplane on lake." https://free-images.com/display/transportation_airplane_on_lake.html (accessed Nov. 16, 2021).
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