| Acronym: NSCBRRI |
| Main Objective: This project will address new, statistically based methods for image restoration and reconstruction. The fundamental approach consists of using representations of natural images yielding sparse and near-independent coefficients. This goal will be pursued along two main lines: 1. Methods relying on a fixed, wavelet-based representation. The project shall extend existing methods of denoising, and of deblurring using a known blur operator, to the blind deblurring / denoising situation. The main approach will consist of taking the blur operator as an additional unknown in a Bayesian formulation of the problem. 2. Methods relying on a learned, ICA-based, spatially invariant representation. The project shall address new image models, consisting of an i.i.d. source followed by a learned, linear or nonlinear, spatially invariant filter, and their application to the blind deblurring problem. Besides blurred natural images, the project will also address the reconstruction of other classes of images, namely those formed through tomographic methods. |
| Reference: POSC/EEA-CPS/61271/2004 |
| Funding: FCT/POSC |
| Start Date: 01-08-2005 |
| End Date: 31-07-2008 |
| Team: Luís Henrique Martins Borges de Almeida, José Manuel Bioucas Dias, Mario Alexandre Teles de Figueiredo, Mariana Sá Correia Leite de Almeida, João Pedro Afonso Oliveira da Silva |
| Groups: Pattern and Image Analysis – Lx |
| Partners: |
| Local Coordinator: Luís Henrique Martins Borges de Almeida |
| Links: Internal Page |
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Associated Publications
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