Enhancing Resolution Along Multiple Imaging Dimensions Using Assorted Pixels
IEEE Transactions on Pattern Analysis and Machine Intelligence
Figures of merit for color scanners
IEEE Transactions on Image Processing
Color plane interpolation using alternating projections
IEEE Transactions on Image Processing
Linear demosaicing inspired by the human visual system
IEEE Transactions on Image Processing
Spatio-Spectral Color Filter Array Design for Optimal Image Recovery
IEEE Transactions on Image Processing
Computational plenoptic imaging
ACM SIGGRAPH 2012 Courses
A unified framework for multi-sensor HDR video reconstruction
Image Communication
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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.