Abstract
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.
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Nakazaki, K., Murakami, Y., Yamaguchi, M. (2014). Hybrid-Resolution Spectral Imaging System Using Adaptive Regression-Based Reconstruction. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds) Image and Signal Processing. ICISP 2014. Lecture Notes in Computer Science, vol 8509. Springer, Cham. https://doi.org/10.1007/978-3-319-07998-1_17
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DOI: https://doi.org/10.1007/978-3-319-07998-1_17
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