论文标题
NTIRE 2020挑战RGB图像的光谱重建挑战
NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image
论文作者
论文摘要
本文回顾了RGB图像中光谱重建的第二项挑战，即从3通道RGB图像中恢复全景高光谱（HS）信息。与以前的挑战一样，提供了两条曲目：（i）从无噪声RGB估算HS图像的“干净”曲目，使用接地真实的HS图像和提供的光谱敏感性功能（II）“真实世界”轨道，通过未知且未知的摄像头模拟了HS图像，将RGB图像本身进行数值计算，并恢复了HS图像。提出了一个新的，超过有史以来的自然高光谱图像数据集，其中包含510 HS图像。清洁和现实世界的曲目分别有103和78个注册参与者，有14支球队参加了最后的测试阶段。还提供了对拟议方法的描述，以及他们的挑战得分以及对最高表现方法的广泛评估。他们从RGB图像中评估了光谱重建中的最先进。
This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. As in the previous challenge, two tracks were provided: (i) a "Clean" track where HS images are estimated from noise-free RGBs, the RGB images are themselves calculated numerically using the ground-truth HS images and supplied spectral sensitivity functions (ii) a "Real World" track, simulating capture by an uncalibrated and unknown camera, where the HS images are recovered from noisy JPEG-compressed RGB images. A new, larger-than-ever, natural hyperspectral image data set is presented, containing a total of 510 HS images. The Clean and Real World tracks had 103 and 78 registered participants respectively, with 14 teams competing in the final testing phase. A description of the proposed methods, alongside their challenge scores and an extensive evaluation of top performing methods is also provided. They gauge the state-of-the-art in spectral reconstruction from an RGB image.
