The fully data driven deconvolution of noisy images is a highly ill-posed problem, where the image, the blur and the noise parameters have to be simultaneously estimated from the data alone. Our approach is to exploit the information related to the image intensity edges both to improve the solution and to significantly redice the computational costs.
Fast fully data-driven image restoration by means of edge-preserving regularization
Tonazzini A
2001
Abstract
The fully data driven deconvolution of noisy images is a highly ill-posed problem, where the image, the blur and the noise parameters have to be simultaneously estimated from the data alone. Our approach is to exploit the information related to the image intensity edges both to improve the solution and to significantly redice the computational costs.File in questo prodotto:
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Descrizione: Fast fully data-driven image restoration by means of edge-preserving regularization
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