Abstract

Capturing hyperspectral images requires expensive andspecialized hardware that is not readily accessible to most users. Digital cameras, on the other hand, are significantlycheaper in comparison and can be easily purchased and used. In this paper, we present a framework for reconstruct-ing hyperspectral images by using multiple consumer-level digital cameras. Our approach works by exploiting the dif-ferent spectral sensitivities of different camera sensors. Inparticular, due to the differences in spectral sensitivities of the cameras, different cameras yield different RGB mea-surements for the same spectral signal. We introduce analgorithm that is able to combine and convert these differ-ent RGB measurements into a single hyperspectral imagefor both indoor and outdoor scenes. This camera-based ap-proach allows hyperspectral imaging at a fraction of the cost of most existing hyperspectral hardware. We validate the accuracy of our reconstruction against ground truth hyperspectral images (using both synthetic and real cases)and show its usage on relighting applications.