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 …

Monitoring agriculture from satellite remote sensing data, such as multispectral images, has
become a powerful tool since it has demonstrated a great potential for providing timely and …

The scarcity and low spatial resolution of hyperspectral images (HSIs) have become a major
problem limiting the application of the images. In recent years, spectral reconstruction (SR) …

Image fusion is a technique of combining two or more images into a single image which is
more informative from an interpretation point of view. With the rapid development of different …

This paper proposes a snapshot Compressed Light Field Imaging Spectrometer based on
compressed sensing and light field concept, which can acquire the two-dimensional spatial …

In the compressive spectral imaging (CSI) framework, different architectures have been
proposed to recover high-resolution spectral images from compressive measurements …

Spectral image classification uses the huge amount of information provided by spectral
images to identify objects in the scene of interest. In this sense, spectral images typically …

Depth–spectral imaging (DSI) is an emerging technology which can obtain and reconstruct
the spatial, spectral and depth information of a scene simultaneously. Conventionally, DSI …

Object imaging and recognition under difficult visual conditions is extremely challenging due
to the captured low-quality images, and traditional optical-based recognition methods …

Multi-sensor image can provide supplementary information, usually leading to better
performance in classification tasks. However, the general deep neural network-based multi …