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

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.