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We present an efficient approach for high-quality non-blind deconvolution based on the use of sparse adaptive priors. Its regularization term enforces preservation of strong edges while removing noise. We model the image-prior deconvolution problem as a linear system, which is solved in the frequency domain. This clean formulation lends to a simple and efficient implementation. We demonstrate its...
We present a coded‐aperture method based on a family of masks obtained as the convolution of one “hole” with a structural component consisting of an arrangement of Dirac delta functions. We call the arrangement of delta functions the structural component of the mask, and use it to efficiently encode scene distance information. We illustrate the potential of our approach by analyzing a family of masks...
Computational photography tries to expand the concept of traditional photography (a static two dimensional projection of a scene) using state-of-the-art technology. While this can be achieved by combining information from multiple conventional pictures, a more interesting challenge consists in encoding and recovering additional information from one (or more) image(s). Since a photograph results from...
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