Titlebook: 3-D Shape Estimation and Image Restoration; Exploiting Defocus a Paolo Favaro,Stefano Soatto Book 2007 Springer-Verlag London 2007 3D.3D Mo

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978-1-84996-559-0Springer-Verlag London 2007

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Rolf Joachim Nessel,Gerhard Wilmesasks. Even relatively “unintelligent” animals can easily navigate through unknown, complex, dynamic environments, avoid obstacles, and recognize prey or predators at a distance. Skilled humans can view a scene and reproduce a model of it that captures its shape (sculpture) and appearance (painting)

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Compatriot

https://doi.org/10.1007/978-3-322-88193-9under a certain focus setting, summarized in equation (2.4). Our main concern from now on is to use this equation to try to infer shape and radiance given a number of images taken with different settings. Before we venture into the design of algorithms to infer shape and radiance from blurred images

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https://doi.org/10.1007/978-3-322-88247-9 the ideal image and the measured one is additive Gaussian noise. This assumption is clearly not germane, because it admits the possibility that the measured image is negative. In fact, given a large enough variance of the noise ., even if the ideal image . is positive, one cannot guarantee that the

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