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Showing 1 to 4 of 4 for “"Constrained Imaging"”.
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Constrained imaging: denoising and sparse sampling
Made available in DSpace on 2011-05-25T14:59:20Z (GMT). No. of bitstreams: 2 Haldar_Justin.pdf: 25586752 bytes, checksum: 13b473014d3b4c607a03de95d1f71669 (MD5) license.txt: 4061 bytes, checksum: 1d9342c42cf91c0d9be87c7868170d96 (MD5)
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Compressive image feature extraction by means of folding
… The application is in size weight and power constrained imaging scenarios where an efficient implementation of this dimensionality reduction can save power and computation costs. The specific features we explore are image corners, rotation, and translation. We present algorithms for …
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Ocular Biometrics: Human Recognition in Challenging Conditions
… been shown to be effectively unique under ideal imaging conditions. However, as imaging constraints are relaxed, the iris becomes increasingly difficult to image, dra- matically decreasing its usability as an accurate biometric. Ocular recognition has been recently proposed as a way to complement …
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Fast MRI with sparse sampling: models, algorithms, and applications
Conventional magnetic resonance imaging (MRI) methods are based on the Shannon-Nyquist sampling theorem. The number of required Nyquist samples grows exponentially with respect to the underlying physical dimension of the imaging problem, resulting in significant difficulty of achieving high …