Uma abordagem híbrida baseada em Projeções sobre Conjuntos Convexos para Super-Resolução espacial e espectral

• Ano de defesa: 2016
• Autor(a) principal: Cunha, Bruno Aguilar
• Orientador(a): Homem, Murillo Rodrigo Petrucelli
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus Sorocaba
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação - PPGCC-So
• Palavras-chave em Português: Super-Resolução de imagens; Projeção sobre Conjuntos Convexos; Abordagem Espectral e Espacial; Abordagem Híbrida; Algoritmos computacionais
• Palavras-chave em Inglês: Image Super-Resolution; Projection Onto Convex Sets; Hybrid Approach; Spectral and Spatial Approach; Computer algorithms
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/9159

This work proposes both a study and a development of an algorithm for super-resolution of digital images using projections onto convex sets. The method is based on a classic algorithm for spatial super-resolution which considering the subpixel information present in a set of lower resolution images, generate an image of higher resolution and better visual quality. We propose the incorporation of a new restriction based on the Richardson-Lucy algorithm in order to restore and recover part of the spatial frequencies lost during the degradation and decimation process of the high resolution images. In this way the algorithm provides a hybrid approach based on projections onto convex sets which is capable of promoting both the spatial and spectral image super-resolution. The proposed approach was compared with the original algorithm from Sezan and Tekalp and later with a method based on a robust framework that is considered nowadays one of the most effective methods for super-resolution. The results, considering both the visual and the mean square error analysis, demonstrate that the proposed method has great potential promoting increased visual quality over the images studied.