Probabilistic Decision Based Average Trimmed Filter for the Removal of High-Density Salt and Pepper Noise
Amit Prakash Sen1, Nirmal Kumar Rout2
1Amit Prakash Sen*, School of Electronics Engineering, KIIT University, Bhubaneswar, India.
2Nirmal Kumar Rout, School of Electronics Engineering, KIIT University, Bhubaneswar, India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4350-4357 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6739018520/2020©BEIESP | DOI: 10.35940/ijrte.E6739.018520
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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: The paper focuses on the evacuation of salt and pepper noise from a contaminated image. A probabilistic decision based average trimmed filter (PDBATF) is proposed for both high and low noise density. The proposed algorithm addresses the issue related to even number of noise-free pixel in trimmed median filter for the calculation of processing pixel. The proposed average trimmed filter is incorporated for low noise density while the proposed patch else average trimmed filter is applied for high noise density. Finally, they are combined together to develop the proposed PDBATF. The proposed algorithm show an excellent noise removal capability compared to the recently developed algorithms in terms of peak signal to noise ratio, image enhancement factor, mean absolute error and execution time. It works very efficiently in de-noising contaminated medical images such as chest-x-ray and malaria-blood-smear.
Keywords: Medical Image De-Noising; Salt And Pepper Noise; Noise Removal; Trimmed Median Filter; Probabilistic Approach.
Scope of the Article: Signal and Image Processing.