In2SET: Intra-Inter Similarity Exploiting Transformer for Dual-Camera
  Compressive Hyperspectral Imaging
Xin Wang Lizhi Wang Xiangtian Ma Maoqing Zhang Lin Zhu Hua Huang
Dual-Camera Compressed Hyperspectral Imaging (DCCHI) offers the capability to
reconstruct 3D Hyperspectral Image (HSI) by fusing compressive and Panchromatic
(PAN) image, which has shown great potential for snapshot hyperspectral imaging
in practice. In this paper, we introduce a novel DCCHI reconstruction network,
the Intra-Inter Similarity Exploiting Transformer (In2SET). Our key insight is
to make full use of the PAN image to assist the reconstruction. To this end, we
propose using the intra-similarity within the PAN image as a proxy for
approximating the intra-similarity in the original HSI, thereby offering an
enhanced content prior for more accurate HSI reconstruction. Furthermore, we
aim to align the features from the underlying HSI with those of the PAN image,
maintaining semantic consistency and introducing new contextual information for
the reconstruction process. By integrating In2SET into a PAN-guided unrolling
framework, our method substantially enhances the spatial-spectral fidelity and
detail of the reconstructed images, providing a more comprehensive and accurate
depiction of the scene. Extensive experiments conducted on both real and
simulated datasets demonstrate that our approach consistently outperforms
existing state-of-the-art methods in terms of reconstruction quality and
computational complexity. Code will be released.