Physically Plausible Spectral Reconstruction

Lin, Yi-tun and Finlayson, Graham D. (2020) Physically Plausible Spectral Reconstruction. Sensors, 20 (21). ISSN 1424-8220

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Abstract

Spectral reconstruction algorithms recover spectra from RGB sensor responses. Recent methods—with the very best algorithms using deep learning—can already solve this problem with good spectral accuracy. However, the recovered spectra are physically incorrect in that they do not induce the RGBs from which they are recovered. Moreover, if the exposure of the RGB image changes then the recovery performance often degrades significantly—i.e., most contemporary methods only work for a fixed exposure. In this paper, we develop a physically accurate recovery method: the spectra we recover provably induce the same RGBs. Key to our approach is the idea that the set of spectra that integrate to the same RGB can be expressed as the sum of a unique fundamental metamer (spanned by the camera’s spectral sensitivities and linearly related to the RGB) and a linear combination of a vector space of metameric blacks (orthogonal to the spectral sensitivities). Physically plausible spectral recovery resorts to finding a spectrum that adheres to the fundamental metamer plus metameric black decomposition. To further ensure spectral recovery that is robust to changes in exposure, we incorporate exposure changes in the training stage of the developed method. In experiments we evaluate how well the methods recover spectra and predict the actual RGBs and RGBs under different viewing conditions (changing illuminations and/or cameras). The results show that our method generally improves the state-of-the-art spectral recovery (with more stabilized performance when exposure varies) and provides zero colorimetric error. Moreover, our method significantly improves the color fidelity under different viewing conditions, with up to a 60% reduction in some cases.

Item Type: Article
Uncontrolled Keywords: hyperspectral imaging,multispectral imaging,spectral reconstruction,analytical chemistry,biochemistry,atomic and molecular physics, and optics,instrumentation,electrical and electronic engineering ,/dk/atira/pure/subjectarea/asjc/1600/1602
Faculty \ School: Faculty of Science > School of Computing Sciences
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Depositing User: LivePure Connector
Date Deposited: 13 Nov 2020 01:11
Last Modified: 04 Mar 2021 00:49
URI: https://ueaeprints.uea.ac.uk/id/eprint/77681
DOI: 10.3390/s20216399

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