Abstract Magnetic Resonance Imaging (MRI) typically comes at the cost of small spatial
coverage, high expenses and long scan times. Accelerating MRI acquisition by taking less …

The field of perceptual quality assessment has gone through a wide range of developments
and it is still growing. In particular, the area of no-reference (NR) image and video quality …

Due to the absence of a desirable objective for low-light image enhancement, previous data-
driven methods may provide undesirable enhanced results including amplified noise …

While deep convolutional neural networks (CNNs) have achieved impressive success in
image denoising with additive white Gaussian noise (AWGN), their performance remains …

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which
is highly desirable for numerous clinical applications. This can not only reduce the scanning …

The difficulty of no-reference image quality assessment (NR IQA) often lies in the lack of
knowledge about the distortion in the image, which makes quality assessment blind and …

Compared with traditional seismic noise attenuation algorithms that depend on signal
models and their corresponding prior assumptions, removing noise with a deep neural …

Patient scans from MRI often suffer from noise, which hampers the diagnostic capability of
such images. As a method to mitigate such artifacts, denoising is largely studied both within …

A novel method for anomaly detection in hyperspectral images is proposed. The method is
based on two ideas. First, compared with the surrounding background, objects with …

Most of existing image denoising methods assume the corrupted noise to be additive white
Gaussian noise (AWGN). However, the realistic noise in real-world noisy images is much …