Detalhes bibliográficos
| Ano de defesa: |
2008 |
| Autor(a) principal: |
Ponti Junior, Moacir Pereira |
| Orientador(a): |
Mascarenhas, Nelson Delfino d'Ávila
 |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de São Carlos
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Biotecnologia - PPGBiotec
|
| Departamento: |
Não Informado pela instituição
|
| País: |
BR
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
https://repositorio.ufscar.br/handle/20.500.14289/250
|
Resumo: |
The study of living cells, isolated or in tissues, in several applications, requires the use of microscopy techniques. The fluorescence microscopes are specially important for making possible images with enhancement of specific structures and detection of biological processes. However, microscopes, like other optical systems, corrupt images so that many details are lost after the passage of the image through their optical components. The conventional (wide-field) fluorescence microscopes degrade images mainly on the axial direction, limiting the amount of frequencies that passes through the system. As a result, there is an out-of-focus blur, making it difficult to use the images to obtain three-dimensional (3D) images by computational optical sectioning microscopy (COSM). The main contribution of this thesis is the development of computer-based methods that are able to restore acquired images, through spectrum extrapolation algorithms that restore a portion of the lost frequencies, even in noisy images. A non-linear algorithm was proposed, based on the Richardson-Lucy method, with space and frequency domain constraints as in the Gerchberg-Papoulis algorithm. this method defines an unified algorithm to restore and extrapolate images, focusing on the spatial finite support constraint. The proposed method showed improved extrapolation when compared to previously known methods. Besides, other algorithms were developed based on the proposed method. Each variation of the basic algorithm has distinct features to attenuate the noise, define adaptively the spatial constraint, and detect the image background region. The use of an adaptive constraint and the extraction of information directly from the images were shown to contribute to the recovery of lost frequencies. The results are promising, showing the potential of extrapolation in real conditions, improving the three-dimensional visualization of specimens in wide-field (non-confocal) microscopes, helping many important applications in biotechnology, such as the assessment of cell cultures. |
