Hybrid-resolution spectral imaging is a technique that efficiently produces high-resolution spectral images by combining low-resolution spectral data with a high-resolution RGB image. In this paper, we introduce a regression- based spectral reconstruction method for this system to enable us doing accurate spectral estimation without a laborious measurement of the spectral sensitivity of the RGB camera. We present two methods for regression-based spectral reconstruction that utilize spatially-registered pair of a low-resolution spectral image and a high-resolution RGB image: whole frame data regression and locally weighted regression. In the experiment, we developed a hybridresolution spectral imaging system, and it was confirmed that the regressionbased methods can estimate spectra in high accuracy. © 2014 Springer International Publishing.
CITATION STYLE
Nakazaki, K., Murakami, Y., & Yamaguchi, M. (2014). Hybrid-resolution spectral imaging system using adaptive regression-based reconstruction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8509 LNCS, pp. 142–150). Springer Verlag. https://doi.org/10.1007/978-3-319-07998-1_17
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