Abstract
In recent years, the fusion of high spatial resolution multispectral image (HR-MSI) and low spatial resolution hyperspectral image (LR-HSI) has been recognized as an effective method for HSI super-resolution (HSI-SR). However, both HSI and MSI may be acquired under extreme conditions such as night or poorly illuminating scenarios, which may cause different exposure levels, thereby seriously downgrading the yielded HSISR. In contrast to most existing methods based on respective low-light enhancements (LLIE) of MSI and HSI followed by their fusion, a deep Unfolding HSI Super-Resolution with Automatic Exposure Correction (UHSR-AEC) is proposed, that can effectively generate a high-quality fused HSI-SR (in texture and features) even under very imbalanced exposures, thanks to the correlation between LLIE and HSI-SR taken into account. Extensive experiments are provided to demonstrate the state-of-the-art overall performance of the proposed UHSR-AEC, including comparison with some benchmark peer methods.
Abstract (translated)
近年来，将高空间分辨率多光谱图像（HR-MSI）与低空间分辨率超光谱图像（LR-HSI）的融合被认为是超分辨率（HSI-SR）的有效方法。然而，在极端情况下，如夜间或光线较弱的场景中，HSI和MSI可能被获取，这可能导致不同的曝光水平，从而严重降低HSISR的产率。与大多数基于各自的低光增强方法（LLIE）的MSI和HSI的融合相比，我们提出了一个深度解卷HSI超分辨率与自动曝光校正（UHSR-AEC）相结合的方法，可以在非常不平衡的曝光情况下生成高质量的融合HSI-SR（纹理和特征），因为LLIE和HSI-SR之间的相关性已经考虑到。我们提供了大量实验来证明所提出的UHSR-AEC的尖端整体性能，包括与一些基准同行的比较。
URL
https://arxiv.org/abs/2403.09096
