Decision Tree Based Algorithm for Removal of Different Probability Salt and Pepper Noise in Images
Vasanth K1, Shirisha N2, Naveen Kishore Babu3
1Dr. Vasanth K, Professor, Vidya Jyothi Institute of Technology, Aziz Nagar, Hyderabad (Telengana), India.
2N. Shirisha, PG Scholar, Vidya Jyothi Institute of Technology, Aziz Nagar, Hyderabad (Telengana), India.
3N Naveen Kumar Babu, CEO, Link Buffer Studios, Canada North America.
Manuscript received on 19 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3496-3500 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B14280982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1428.0982S1119
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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: A Decision tree based algorithm for the removal of equal and unequal probability salt and pepper noise in images is proposed. The algorithm aims to address one solution for different salt and pepper noise models. The proposed algorithm operates on an image using fixed 3*3 window. The decision tree based algorithm classifies pixel into noisy or not based on the decision and replaces it with mean of neighbours or unsymmetrical trimmed median or unsymmetrical trimmed midpoint. The algorithm exhibit excellent noise elimination capability at high noise densities in terms of quantitative and qualitative perspective. The algorithm was found to exhibit good noise removal characteristics for three noise models.
Keywords: Salt and Pepper Noise, Impulse Noise, Unequal Probability, Decision Based Algorithm.
Scope of the Article: Algorithm Engineering