Noise is always presents in digital images during image acquisition, coding, transmission,
and processing steps. Noise is very difficult to remove it from the digital images without the …

With the explosion in the number of digital images taken every day, the demand for more
accurate and visually pleasing images is increasing. However, the images captured by …

Background Digital images are captured using sensors during the data acquisition phase,
where they are often contaminated by noise (an undesired random signal). Such noise can …

Removing noise from the original signal is still a challenging problem for researchers. There
have been several published algorithms and each approach has its assumptions …

Getting an efficient method of removing noise from the images, before processing them for
further analysis is a great challenge for the researchers. Noise can degrade the image at the …

In this paper, we present a method for removing noise from digital images corrupted with
additive, multiplicative, and mixed noise. An image patch from an ideal image is modeled as …

The search for efficient image denoising methods still is a valid challenge, at the crossing of
functional analysis and statistics. In spite of the sophistication of the recently proposed …

Noise reduction is a perplexing undertaking for the researchers in digital image processing
and has a wide range of applications in automation, IoT (Internet of Things), medicine, etc …

Image denoising algorithms often assume an additive white Gaussian noise (AWGN)
process that is independent of the actual RGB values. Such approaches are not fully …

At the crossing of the statistical and functional analysis, there exists a relentless quest for an
efficient image denoising algorithm. In terms of greyscale imaging, a plethora of denoising …