NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image

• URL: http://arxiv.org/abs/2005.03412v1
• Date: Thu, 7 May 2020 12:23:56 GMT
• Title: NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image
• Authors: Boaz Arad, Radu Timofte, Ohad Ben-Shahar, Yi-Tun Lin, Graham Finlayson, Shai Givati, and others
• Abstract summary: This paper reviews the second challenge on spectral reconstruction from RGB images. It recovers whole-scene hyperspectral (HS) information from a 3-channel RGB image. A new, larger-than-ever, natural hyperspectral image data set is presented.
• Score: 61.71186808848108
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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