This paper presents a prototype of a spectral video system based on hybrid resolution spectral imaging. The system consists of a commercial three-channel color camera and a low-resolution spectral sensor which captures a 68-pixel spectral image by a single snap-shot. By combining the measurement data from both devices, the system produces high-resolution spectral image data frame by frame. The accuracy of the spectral data measured by the system is evaluated at some selected regions in the image. As a result, it is confirmed that spectra can be measured with less or around 10% of normalized root mean squared error. In addition, the capture of spectral videos in 3 frame-per-second and the real-time color reproduction in the same frame rate from the spectral video are demonstrated.

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.