IEEE Transactions on Image Processing · 2010 · 1.2K citations · 17 references
ArtsVision ScienceComputer VisionDigital ImagingMachine VisionColor ImagingDigital Image ProcessingHigh-dynamic-range ImagingImage ReconstructionImage SamplingScene ReconstructionChannelsColor Filter ArraysDynamic RangeFiltersHigh Dynamic Range (Hdr) ImagingScene Reconstruction From ImagesSpectral Layout
The use of a complex color filter array in a GAP camera leads to severe under‑sampling of some filter types, producing reconstructed images with strong aliasing. The paper proposes a generalized assorted pixel camera that allows post‑capture control of spatial resolution, dynamic range, and spectral detail, and presents an optimization method for filter layout and an algorithm to reconstruct under‑sampled channels while reducing aliasing. The camera employs a complex mosaic of color filters, and the authors develop an optimization framework for its spatial and spectral layout and an algorithm to reconstruct under‑sampled channels, supported by a publicly available multispectral image database. Simulations confirm that a single captured image can be post‑processed to produce monochrome, HDR monochrome, RGB, HDR RGB, and multispectral outputs, demonstrating the GAP camera’s versatility and performance.
We propose the concept of a generalized assorted pixel (GAP) camera, which enables the user to capture a single image of a scene and, after the fact, control the tradeoff between spatial resolution, dynamic range and spectral detail. The GAP camera uses a complex array (or mosaic) of color filters. A major problem with using such an array is that the captured image is severely under-sampled for at least some of the filter types. This leads to reconstructed images with strong aliasing. We make four contributions in this paper: 1) we present a comprehensive optimization method to arrive at the spatial and spectral layout of the color filter array of a GAP camera. 2) We develop a novel algorithm for reconstructing the under-sampled channels of the image while minimizing aliasing artifacts. 3) We demonstrate how the user can capture a single image and then control the tradeoff of spatial resolution to generate a variety of images, including monochrome, high dynamic range (HDR) monochrome, RGB, HDR RGB, and multispectral images. 4) Finally, the performance of our GAP camera has been verified using extensive simulations that use multispectral images of real world scenes. A large database of these multispectral images has been made available at http://wwwl.cs.columbia.edu/ CAVE/projects/gap_camera/ for use by the research community.
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Demosaicking: color filter array interpolation
Bahadır K. Güntürk, John Glotzbach, Y. Altunbasak et al. · IEEE Signal Processing Magazine · 2005 · 578 citations
High dynamic range imaging: spatially varying pixel exposures
S.K. Nayar, Tomoo Mitsunaga · 2002 · 543 citations