Spectral imaging collects and processes information along spatial and spectral coordinates
quantified in discrete voxels, which can be treated as a 3D spectral data cube. The spectral …

Coded aperture snapshot spectral imaging (CASSI) is an important technique for capturing
three-dimensional (3D) hyperspectral images (HSIs), and involves an inverse problem of …

Hyperspectral image (HSI) denoising is a fundamental task in remote sensing image
processing, which is helpful for HSI subsequent applications, such as unmixing and …

This paper proposes a non-data-driven deep neural network for spectral image recovery
problems such as denoising, single hyperspectral image super-resolution, and compressive …

Inverse problems in spectral imaging have been addressed in the state-of-the-art by
encoding scenes to alleviate the ill-posedness, leveraging the knowledge of the forward …

This paper proposes a non-data-driven deep neural network for spectral image recovery
problems such as denoising, single hyperspectral image super-resolution, and compressive …

Hyperspectral compressed imaging is a novel imaging detection technology based on
compressed sensing theory that can quickly acquire spectral information of terrestrial objects …

Deep convolutional neural networks have recently shown promising results in compressive
spectral reconstruction. Previous methods, however, usually adopt a single mapping …

Obtaining a low-spatial-resolution hyperspectral image (HS) or low-spectral-resolution
multispectral (MS) image from a high-resolution (HR) spectral image is straightforward with …

This study extends a self-supervised image denoising technique proposed by the authors to
a more general image restoration method. The previous work was inspired by Ulyanov's …