Constructing high-dynamic-range spectral images for natural scenes

The cutting-edge research in high-dynamic-range (HDR) display, such as inverse tone-mapping operators for HDR TV, HDR image quality (IQ) evaluation, and HDR image enhancement, suffer from a lack of reliable training and testing images. To address this problem, we combined the HDR imaging technique with high-accuracy spectral images to construct a first-of-its-kind HDR spectral radiance image. A framework was presented to capture multi-exposure hyperspectral images of HDR outdoor scenes and establish the HDR spectral image. By employing spectrophotometric calibration, the spectral radiance-based HDR images were created. The metadata of the spectral images provide crucial colorimetry information that was absent in the existing datasets. To validate the superiority of the proposed HDR spectral images in typical applications, the spectral sensitivity functions of a camera equipped with a multispectral-filter-array sensor was optimized, and the IQ evaluation results indicate a better adaptability over existing ones. Furthermore, the HDR image augmentation suggests that it is possible to provide a large number of RGB training images for various research objectives based on the proposed images.