Current advances and future perspectives of image fusion: A comprehensive review
Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …
world than a single modality alone. Infrared images discriminate targets with respect to their …
A review of snapshot multidimensional optical imaging: measuring photon tags in parallel
Multidimensional optical imaging has seen remarkable growth in the past decade. Rather
than measuring only the two-dimensional spatial distribution of light, as in conventional …
than measuring only the two-dimensional spatial distribution of light, as in conventional …
Mask-guided spectral-wise transformer for efficient hyperspectral image reconstruction
Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-spectral signal from
a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system. The …
a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system. The …
Coarse-to-fine sparse transformer for hyperspectral image reconstruction
Many learning-based algorithms have been developed to solve the inverse problem of
coded aperture snapshot spectral imaging (CASSI). However, CNN-based methods show …
coded aperture snapshot spectral imaging (CASSI). However, CNN-based methods show …
End-to-end low cost compressive spectral imaging with spatial-spectral self-attention
Coded aperture snapshot spectral imaging (CASSI) is an effective tool to capture real-world
3D hyperspectral images. While a number of existing work has been conducted for …
3D hyperspectral images. While a number of existing work has been conducted for …
l-net: Reconstruct hyperspectral images from a snapshot measurement
We propose the l-net, which reconstructs hyperspectral images (eg, with 24 spectral
channels) from a single shot measurement. This task is usually termed snapshot …
channels) from a single shot measurement. This task is usually termed snapshot …
Hyperspectral image reconstruction using a deep spatial-spectral prior
Regularization is a fundamental technique to solve an ill-posed optimization problem
robustly and is essential to reconstruct compressive hyperspectral images. Various hand …
robustly and is essential to reconstruct compressive hyperspectral images. Various hand …