Local adaptable quadrature filters to demodulate single fringe patterns with closed fringes
We propose a new approach to demodulate a single fringe pattern with closed fringes by using Local Adaptable Quadrature Filters (LAQF). Quadrature filters have been widely used to demodulate complete image interferograms with carrier frequency. However, in this paper, we propose the use of quadratur...
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2007 |
| País: | México |
| Recursos: | Centro de Investigación en Matemáticas |
| Repositório: | Repositorio Institucional CIMAT |
| Idioma: | inglês |
| OAI Identifier: | oai:cimat.repositorioinstitucional.mx:1008/892 |
| Acesso em linha: | http://cimat.repositorioinstitucional.mx/jspui/handle/1008/892 |
| Access Level: | Acceso aberto |
| Palavra-chave: | info:eu-repo/classification/MSC/Redes Neuronales info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/12 info:eu-repo/classification/cti/1203 info:eu-repo/classification/cti/120304 |
| Resumo: | We propose a new approach to demodulate a single fringe pattern with closed fringes by using Local Adaptable Quadrature Filters (LAQF). Quadrature filters have been widely used to demodulate complete image interferograms with carrier frequency. However, in this paper, we propose the use of quadrature filters locally, assuming that the phase is locally quasimonochromatic, since quadrature filters are not capable to demodulate image interferograms with closed fringes. The idea, in this paper, is to demodulate the fringe pattern with closed fringes sequentially, using a fringe following scanning strategy. In particular we use linear robust quadrature filters to obtain a fast and robust demodulation method for single fringe pattern images with closed fringes. The proposed LAQF method does not require a previous fringe pattern normalization. Some tests with experimental interferograms are shown to see the performance of the method along with comparisons to its closest competitor, which is the Regularized Phase Tracker (RPT), and we will see that this method is tolerant to higher levels of noise. |
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