A compact, low-cost, single-shot hyperspectral imaging method has been devised, which captures images using a conventional DSLR camera equipped with an ordinary refractive prism placed in front of the lens. The new, user-friendly method was tested on a variety of natural scenes, and the results, according to the researchers, compared well with current state-of-the-art hyperspectral imaging systems, achieving quality images without compromising accuracy. A close-up inset that the researchers capture and use as an input image for running their algorithm. Courtesy of ACM SIGGRAPH ASIA. The setup operates without the coded aperture mask and large optical components typical in professional setups, which could limit available spectral cues. To remedy this, researchers from Korea Advanced Institute of Science and Technology (KAIST) and Universidad de Zaragoza developed an image formulation model that predicts the perspective projection of dispersion of light, yielding the dispersion direction and magnitude of each wavelength at every pixel. Researchers also developed a reconstruction algorithm that can estimate the full spectral information of a scene from sparse information, addressing edge restoration of the scene being captured, gradient estimation, and the spectral resolution of the image. To compare the predictions of their dispersion model with those of professional optics simulation software, the researchers placed a prism in front of a 50 mm lens of a digital camera and captured a point at a distance of 700 mm. They were able to accurately predict dispersion at every pixel using their method, and were able to produce results comparable to professional physical simulation of light transport. The novel technique, which also comprises a novel calibration method to estimate the spatially varying dispersion of the prism, enables users to capture spectral information without requiring a large system setup with various optical components. “Hyperspectral imaging systems are generally built for specific purposes such as aerial remote sensing, or military applications, and as such they are not affordable nor practical for ordinary users,” said Min H. Kim, associate professor of computer science at KAIST. “Our system requires no advanced skills, and we are able to obtain hyperspectral images at virtually full resolution while making hyperspectral imaging practical.” In future work, the team plans to address the system’s current sensitivity to noise as well as performance limitations due to lighting and surfaces without edges of a scene or object. The research was presented at SIGGRAPH Asia 2017 in Bangkok, November 27-30, 2017.