Restauração das imagens do satélite CBERS-1 utilizando POCS

• Ano de defesa: 2005
• Autor(a) principal: Papa, João Paulo
• Orientador(a): Mascarenhas, Nelson Delfino d'Ávila
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação - PPGCC
• País: BR
• Palavras-chave em Português: Processamento de imagens; Restauração de imagens; POCS; Sensoriamento remoto
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/608

The number of applications in remote sensing has widely increased in the last years. The reason for this is mainly the high quality of imaging systems onboard. Among this new generation of satellites, the CBERS-1 (China-Brazil Earth Resources Satellite) was developed through a partnership between Brazil and China, and its main mission is to capture high-resolution images of the Earth using panchromatic and multispectral detectors. However, the information provided by remote sensing needs to be processed to better reflect the radiometric quality of the data, using for this purpose a technique called image restoration. The main goal of image restoration is the reconstruction or recovery of the degraded image using some a priori knowledge of the degradation phenomenon. In this work we developed five image restoration algorithms based on the theory of convex projections, which were obtained through the CBERS-1 band 2 CCD sensor. These algorithms are based on the application of restrictions in convex sets form, through the POCS (Projections Onto Convex Sets) method, where the intersection among these sets, if it exists, gives a satisfactory solution for the problem. The simulations were developed using the RAP (Row-Action Projections), the SIRT (Simultaneous Iterative Reconstruction Technique) and an algorithm that uses prototype image constraints, which were obtained by the methods cited above and by the MIF (Modified Inverse Filter). The results were visually and numerically evaluated.