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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.

Accurate color image reproduction under arbitrary illumination can be realized if the spectral reflectance functions in a scene are obtained. Although multispectral imaging is one of the promising methods to obtain the reflectance of a scene, it is expected to reduce the number of color channels without significant loss of accuracy. This paper presents what we believe to be a new method for estimating spectral reflectance functions from color image and multipoint spectral measurements based on maximum a posteriori (MAP) estimation. Multipoint spectral measurements are utilized as auxiliary information to improve the accuracy of spectral reflectance estimated from image data. Through simulations, it is confirmed that the proposed method improves the estimation accuracy, particularly when a scene includes subjects that belong to various categories.

Nonlinear estimation method of spectral reflectance from camera responses is proposed. The proposed method minimizes the mean square error of spectral reflectance when the reflectance can be regarded as a random sequence of Gaussian mixture distribution. In computer simulations, 168 samples of spectral reflectance from a color chart are estimated from their image signals obtained by three- and six-band cameras. It is confirmed that the proposed method improves the accuracy in comparison with the conventional Wiener estimation method.