| Paper: | TP-P1.4 |
| Session: | Interpolation and Superresolution II |
| Time: | Tuesday, September 18, 14:30 - 17:10 |
| Presentation: |
Poster
|
| Title: |
SUPER-RESOLUTION IMAGE RECONSTRUCTION USING THE ICM ALGORITHM |
| Authors: |
Ana Luísa Dine Martins; Universidade Federal de São Carlos | | |
| | Murillo Homem; Universidade Federal de São Carlos | | |
| | Nelson Mascarenhas; Universidade Federal de São Carlos | | |
| Abstract: |
Super-resolution image reconstruction is a powerful methodology for resolution enhancement from a set of blurred and noisy low-resolution images. Following a Bayesian framework, we propose a procedure for super-resolution image reconstruction based on Markov random fields (MRF), where a Potts-Strauss model is assumed for the a priori probability density function of the actual image. The first step is given by aligning all the low-resolution observations over a high resolution grid and then improving the resolution through the Iterated Conditional Modes (ICM) algorithm. The method was analyzed considering a number of simulated low-resolution and globally translated observations and the results demonstrate the effectiveness of the algorithm in reconstructing the desirable high-resolution image. |
