Removal of High Density Salt and Pepper Noise through Modified Decision Based Unsymmetric Trimmed Adaptive Median Filter
Vivek Chandra1, Sagar Deokar2, Siddhant Badhe3, Rajesh Yawle4
1Vivek Chandra, Department of Electronics and Telecommunication, Sinhgad Academy of Engineering, University of Pune, India.
2Sagar Deokar, Department of Electronics and Telecommunication, Sinhgad Academy of Engineering, University of Pune, India.
3Siddhant Badhe, Department of Electronics and Telecommunication, Sinhgad Academy of Engineering, University of Pune, India.
4Rajesh Yawle, Department of Electronics and Telecommunication, Sinhgad Academy of Engineering, University of Pune, India.
Manuscript received on January 21, 2013. | Revised Manuscript received on February 10, 2013. | Manuscript published on February 28, 2013. | PP: 495-499 | Volume-2 Issue-3, February 2013. | Retrieval Number: C1196022313/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An algorithm based on adaptive and unsymmetric trimmed median filter is proposed in this paper. This algorithm is proposed for restoration of gray-scale as well as color images which are highly corrupted by salt and pepper noise. The proposed algorithm replaces the noisy pixel by a value which is either a mean or a median of all other non-noisy pixels in the selected window. The proposed algorithm also adaptively controls the window size depending on the relative amount of noisy pixels compared to non-noisy pixels in the selected window. This proposed algorithm substantially outperforms all existing median-based filters, in terms of suppressing salt and pepper noise while preserving image details. The proposed algorithm is tested against different gray-scale and color images giving better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF) at different noise densities.
Keywords: Adaptive, median filter, restoration, salt and pepper noise.