High-density salt & pepper noise removal using machine learning

This paper proposes an additional ‘Median Layer’ to the existing Convolutional Neural Network (CNN).The work primarily focuses on removing ‘High Density Impulse Noise’ present in an image. The proposed median layer performs median filtering on all feature channels. The developed network is an end-to-end network that does not require any non-trivial preprocessing tasks. Based on the experiments performed, results show that, by inserting a median layer to a CNN, the proposed architecture has given convincing results, when compared to the existing approaches.