Affiliation:
1. KAIST
2. Universidad de Zaragoza
Abstract
We present a novel, compact single-shot hyperspectral imaging method. It enables capturing hyperspectral images using a conventional DSLR camera equipped with just an ordinary refractive prism in front of the camera lens. Our computational imaging method reconstructs the full spectral information of a scene from dispersion over edges. Our setup requires no coded aperture mask, no slit, and no collimating optics, which are necessary for traditional hyperspectral imaging systems. It is thus very cost-effective, while still highly accurate. We tackle two main problems: First, since we do not rely on collimation, the sensor records a projection of the dispersion information, distorted by perspective. Second, available spectral cues are sparse, present only around object edges. We formulate an image formation model that can predict the perspective projection of dispersion, and a reconstruction method that can estimate the full spectral information of a scene from sparse dispersion information. Our results show that our method compares well with other state-of-the-art hyperspectral imaging systems, both in terms of spectral accuracy and spatial resolution, while being orders of magnitude cheaper than commercial imaging systems.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design
Cited by
64 articles.
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