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 …

The current literature documents a plethora of image denoising techniques in the fields of
medical imaging, remote sensing, biometrics, surveillance and vegetation map** …

Block-matching and 3D filtering algorithm (BM3D) is the current state-of-the-art for image
denoising. This algorithm has a high capacity to achieve better noise removal results as …

Synthetic aperture radar (SAR) images often interfere with speckle artifacts that have a great
impact on subsequent processing and analysis operations. To remove speckle artifacts, this …

Traditional image denoising methods, which do not depend on data training, have good
interpretability. However, traditional image denoising methods hardly achieve the denoising …

Crack detection is an important task to monitor the structural health of the infrastructure
exposed to fire. The manual inspections are time consuming and the outcome depends on …

Crack is the external expression form of potential safety risks in bridge construction.
Currently, automatic detection and segmentation of bridge cracks remains the top priority of …

In the COVID-19 era, it may be possible to detect COVID-19 by detecting lesions in scans, ie,
ground-glass opacity, consolidation, nodules, reticulation, or thickened interlobular septa …

Image denoising is one of the fundamental image processing problem. Images are
corrupted with additive white Gaussian noise during image acquisition and transmission …

Many noise removal algorithms have been introduced so far for denoising of MRI images
like a bilateral filter, wavelet transform, maximum likelihood, non-local means, etc. All the …