BM3D is a recent denoising method based on the fact that an image has a locally sparse
representation in transform domain. This sparsity is enhanced by grou** similar 2D image …

Recent state-of-the-art image denoising methods use nonparametric estimation processes
for 8*8 patches and obtain surprisingly good denoising results. The mathematical and …

Arguably several thousands papers are dedicated to image denoising. Most papers assume
a fixed noise model, mainly white Gaussian or Poissonian. This assumption is only valid for …

Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for
the development of robust automated distress evaluation systems that comprise a low-cost …

The current state-of-the-art non-local algorithms for image denoising have the tendency to
remove many low contrast details. Frequency-based algorithms keep these details, but on …

Recent studies have shown that the performance of image denoising methods can be
improved significantly by using deep convolutional neural networks (CNN). The traditional …

Denoising is the problem of removing the inherent noise from an image. The standard noise
model is additive white Gaussian noise, where the observed image f is related to the …

To address the challenges associated with nonlinearity, non-stationarity, susceptibility to
redundant noise interference, and the difficulty in extracting fault feature signals from rolling …

Camera calibration is essential for accurate product visual inspection. In this paper, a novel
efficient camera calibration approach based on K-Singular Value Decomposition (K-SVD) …

The Gaussian mixture is a patch prior that has enjoyed tremendous success in image
processing. In this work, by using Gaussian factor modeling, its dedicated expectation …