This review article provides a comprehensive survey on state-of-the-art impulse and
Gaussian denoising filters applied to images and summarizes the progress that has been …

The advent of deep learning has brought a revolutionary transformation to image denoising
techniques. However, the persistent challenge of acquiring noise-clean pairs for supervised …

Recent studies have shown that deep networks can achieve promising results for image
denoising. However, how to simultaneously incorporate the valuable achievements of …

In surveillance, monitoring and tactical reconnaissance, gathering visual information from a
dynamic environment and accurately processing such data are essential to making informed …

Deep learning methods have shown remarkable performance in image denoising,
particularly when trained on large-scale paired datasets. However, acquiring such paired …

Previous median-based impulse detection strategies tend to work well for fixed-valued
impulses but poorly for random-valued impulse noise, or vice versa. This letter devises a …

A new impulse noise detection technique for switching median filters is presented, which is
based on the minimum absolute value of four convolutions obtained using one-dimensional …

A novel switching median filter incorporating with a powerful impulse noise detection
method, called the boundary discriminative noise detection (BDND), is proposed in this …

The elimination of noise from images becomes a trending field in image processing.
Imagesmay got corrupted by random change in pixel intensity, illumination, or due to poor …

This brief proposes a generalized framework of median based switching schemes, called
multi-state median (MSM) filter. By using a simple thresholding logic, the output of the MSM …