A transformada de Fourier quântica aproximada e sua simulação

• Ano de defesa: 2006
• Autor(a) principal: Marquezino, Franklin de Lima
• Orientador(a): Portugal, Renato
• Banca de defesa: Garcia, Eduardo Lúcio Mendes , Giraldi, Gilson Antonio , Helayël Neto, Jose Abdalla , Lavor, Carlile Campos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Laboratório Nacional de Computação Científica
• Programa de Pós-Graduação: Programa de Pós-Graduação em Modelagem Computacional
• Departamento: Serviço de Análise e Apoio a Formação de Recursos Humanos
• País: BR
• Palavras-chave em Português: Computação Quântica; Algoritmos quânticos; Simulação
• Palavras-chave em Inglês: Quantum computing; Simulation
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://tede.lncc.br/handle/tede/9

Main memory limitations can lower the performance of segmentation applications for large images or even make it undoable. In this work we integrate the T-Surfaces model and Out-of-Core isosurface generation methods in a general framework for segmentation of large image volumes. T-Surfaces is a parametric deformable model based on a triangulation of the image domain, a discrete surface model and an image threshold. Isosurface generation techniques have been implemented through an Out-of-Core method that uses a kd-tree structure, called Meta-Cell technique. By using the Meta-Cell framework, we present an Out-of-Core version of a segmentation method based on T-Surfaces and isosurface extraction. The Gradient Vector Flow (GVF) is an approach based on Partial Differential Equations. This method has been applied together with snake models for image segmentation through boundary extraction. The key idea is to use a diffusion-reaction PDE in order to generate a new external force field that makes snake models less sensitivity to initialization as well as improves the snakes ability to move into boundary concavities. In this work, we firstly review basic results about global optimization conditions of the GVF and numerical considerations of usual GVF schemes. Besides, we present an analytical analysis of the GVF and a frequency domain analysis, which gives elements to discuss the dependency from the parameter values. Also, we discuss the numerical solution of the GVF based in a SOR method. We observe that the model can be used for Multiply Connected Domains and applied an image processing approach in order to increase the GVF efficiency.