Performance Analysis of Median Filter With Respect to Different Padding Methods in the Context of Removing Salt and Pepper Noise
DOI:
https://doi.org/10.51983/ajcst-2019.8.3.2732Keywords:
Median Filter, Salt and Pepper Noise, PaddingAbstract
Image Processing is one of the major areas of research. Images are often corrupted with different types of noise such as Gaussian noise, Poisson noise, Salt and Pepper noise, Speckle noise etc.The present work analyses the performance of the median filter with respect to different padding methods in the context of removing salt and pepper noise.Peak Signal-to-Noise ratio and Mean Squared Error have been considered as parameters for performance evaluation. The results obtained show thatthe Peak Signal-toNoise Ratio and Mean Squared Error obtained between the original image and the filtered image obtained by applying median filter with symmetric padding method on the image corrupted with salt and pepper noise is same as the Peak Signal-to-Noise Ratio and Mean Squared Error obtained between the original image and the filtered image obtained by applying median filter with replicate padding method on the image corrupted with salt and pepper noise respectively.
References
The Wikipedia website [Online]. Available at: https://en.wikipedia.org/wiki/Image_noise.html. [1]
The Wikipedia website [Online]. Available at: https://en.wikipedia.org/wiki/Salt-and-pepper_noise.html. [2]
The Mathworks website [Online]. Available at: https://www.mathworks.com/help/images/what-is-image-Filtering-in-the-spatial-domain.html. [3]
The Mathworks website [Online]. Available at: https://www.mathworks.com/help/images/sliding-neighborhood-operations.html. [4]
The Wikipedia website [Online]. Available at: https://www.wikipedia.org/wiki/Medianfilter.html. [5]
The Dartmouth website [Online]. Available at: http://www.dartmouth.edu/doc/id1/html/filtering an image.html. [6]
Pranay Yadav, Prayag Tiwari, and Vivek Kumar, "Comparative Performance Analysis of Image Denoising techniques," International Conference on Innovations in Engineering and Technology, Bangkok, December 25-26, 2013. [7]
R. Srinivas and Satapura Panda, "Performance Analysis of various filters for Image Noise Removal in different Noise Environment," International Journal of Advanced Computer Research, Vol. 3, No. 4, No. 13, December 2013. [8]
Bhawna and Sukhjeet Kaur Ranade, "Performance Analysis of Filter Based Techniques for Image Denoising," International Journal of Computer Science and Technology, Vol. 6, No. 2, April-June 2015. [9]
Ritu Patil and Pratibha Nagaich, "Performance Analysis of Image Denoising with wavelet transform and Median Filter over AWGN channel," International Journal of Advanced Research in Electronics and Communication Engineering, Vol. 4, No. 10, October-2015. [10]
Suman Shrestha, "Image Denoising using New Adaptive Based Median Filter," Signal & Image Processing: An International Journal (SIPIJ), Vol. 5, No. 4, August-2014. [11]
J. Selva Priya and P. Senthil Kumar, "Performance analysis of Linear and Nonlinear Filters for Image Denoising," International Journal of Advance Research in Engineering, Science and Technology, Vol. 5, No. 3, March 2018. [12]
Wang, Zhou and Zhang, "Progressive Switching Median Filter for the removal of Impulse noise from highly corrupted images," IEEE transactions on circuits and Systems: Analog and Digital Signal Processing, February 1999. [13]
Hongjin Ma and Yufeng Nie, "A two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and Adaptive directional mean filter," PLoS One, Vol. 13, No. 10, October 2018. [14]
K.K.V. Toh, H. Ibrahim and M.N. Mahyuddin, "Salt-and-Pepper noise detection and reduction using fuzzy switching median filter," IEEE transactions on Consumer Electronics, Vol. 54, No. 4, November 2008. [15]
Jayanta Das, Bhaswati Das, Jesmine Saikia, and S.R. Nirmala, "Removal of Salt and Pepper Noise using Selective Adaptive Median Filter," International Conference on Accessibility to Digital World, 2010. [16]
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