ew 18(18): e6

Research Article

Model to estimate the salt and pepper noise density level on gray-scale digital image

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  • @ARTICLE{10.4108/eai.12-6-2018.154816,
        author={Rajesh Kanna B and Mohd Shafi Bhat and Vijayalakshmi C and Alex Noel Joseph Raj},
        title={Model to estimate the salt and pepper noise density level on gray-scale digital image},
        journal={EAI Endorsed Transactions on Energy Web and Information Technologies},
        volume={5},
        number={18},
        publisher={EAI},
        journal_a={EW},
        year={2018},
        month={6},
        keywords={Entropy, Salt-Pepper noise, Noise density},
        doi={10.4108/eai.12-6-2018.154816}
    }
    
  • Rajesh Kanna B
    Mohd Shafi Bhat
    Vijayalakshmi C
    Alex Noel Joseph Raj
    Year: 2018
    Model to estimate the salt and pepper noise density level on gray-scale digital image
    EW
    EAI
    DOI: 10.4108/eai.12-6-2018.154816
Rajesh Kanna B1,*, Mohd Shafi Bhat2, Vijayalakshmi C3, Alex Noel Joseph Raj4
  • 1: Associate Professor, School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India
  • 2: GE Health care, Bengaluru, India
  • 3: Associate Professor, School of Advance Sciences, Vellore Institute of Technology,Chennai, India
  • 4: Department of Electronic Engineering, Shantou University, China
*Contact email: rajeshkanna.b@vit.ac.in

Abstract

In this research paper, we proposed a probabilistic analysis to find the relationship between entropy of image and salt & pepper noise density. For this estimation, we have employed entropy inspection of spatial domain technique. Based on the fact that entropy of image signal decreases with increase in noise density and this decreasing relationship between noise and entropy is robust to individual images traits. In this work, we exploited the entropy values of noisy image with respect to its noise density, and analyzed that such relation is robust to individual images. Further, we considered such relationships for estimation of noise level. Based on the numerical calculations and graphical representations it reveals to the fact that the error is reduced to 8.9% which can be considered as an appropriate model to estimate the salt and pepper noise density.