Comparison of algorithms for the removal of impulsive noise from an image

Abstract

Image pre-processing is an important operation that is used to redefine an image to improve human visual perception and information extraction. To de-noise an image tainted with impulsive noise, several state-of-the-art methods have been presented. This work examines and compares several de-noising methods based on the median filter and its advanced non-linear techniques. The research also focuses on the recommended implementation methodologies for using deep learning to de-noise impulsive noise. The paper focuses on one approach's limitations and possible remedies, as well as other techniques that have been offered. The study also identifies several other difficulties that have yet to be resolved.

Keywords

• Image de-noising
• Noise removal
• Impulsive noise
• Median filter
• Trimmed filter
• Adaptive median filter