In this paper, a novel denoising approach based on optimal trilateral filtering using Grey
Wolf Optimization (GWO) is proposed. At first, a database of noisy images are generated by …

The total variation (TV) regularization model for image restoration is widely utilized due to its
edge preservation properties. Despite its advantages, the TV regularization can obtain …

Image denoising problem still remains an active research field in the image processing. To
improve the denoising quality, it is very important to describe the local structure of the image …

Speckle denoising can improve digital holographic interferometry phase measurements but
may affect experimental accuracy. A deep-learning-based speckle denoising algorithm is …

In this paper, a mixed-order image denoising algorithm containing fractional-order and high-
order regularization terms is proposed, which effectively suppresses the staircase effect …

In this paper, a local activity measurement of the clipped and normalized variance or
standard deviation is proposed to drive anisotropic diffusion and relative total variation …

Blind image deblurring is a very challenging inverse problem due to the severe ill-
posedness caused by the unknown kernel and the latent clear image. To tackle this …

Haze removal, also known as image dehazing, plays an important role in image/video
processing and computer vision applications. Its main purpose is to eliminate haze to …

In this paper by exploiting the theory of wavelet transform, a solution of Laplace equation,
after changing certain initial conditions in terms of wavelet transformation is obtained. We …

Convolutional neural networks (CNNs) have made great achievements in the field of image
denoising but can still be improved. We introduce a network structure, namely, multifeature …