Hybrid-Resolution Spectral Imaging System Using Adaptive Regression-Based Reconstruction

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 hybrid-resolution spectral imaging system, and it was confirmed that the regression-based methods can estimate spectra in high accuracy.