Soft-threshold histogram weighted filtering with correlativity for high density salt-pepper noise images

We proposed a histogram weighted filtering algorithm with soft-threshold for images heavily corrupted by salt-pepper impulse noise. It was based on the correlativity principle of image pixel gray. The neighboring correlativity coefficient was defined to identify noisy pixels and adaptively adjust the filtering intensity. Theoretical and experimental results show that the proposed algorithm has great performances for filtering out impulse noise in extremely corrupted images by high density salt-pepper noise.