Hyperspectral images (HSIs) have been widely used for target detection due to their abundant spatial and spectral information. In this article, a shadow-insensitive hyperspectral target detection (HTD) framework based on exposure fusion is proposed, which consists of the following major steps. First, the input HSI is divided into two parts, namely the shadow region and the nonshadow region. Second, total variation-based feature extraction and overexposure operation are performed on the input image to produce two feature images, i.e., the original feature image and the overexposure image. Third...
