Multiframe image superresolution has been an active research area for many years. In this approach image processing techniques are used to combine multiple low-resolution (LR) images capturing different views of an object. These multiple images are generally under-sampled, degraded by optical and pixel blurs, and corrupted by measurement noise. We exploit diversities in the imaging channels, namely, the number of cameras, magnification, position, and rotation, to undo degradations. Using an iterative back-projection (IBP) algorithm we quantify the improvements in image fidelity gained by using multiple frames compared to single frame, and discuss effects of system parameters on the reconstruction fidelity. As an example, for a system in which the pixel size is matched to optical blur size at a moderate detector noise, we can reduce the reconstruction root-mean-square-error by 570% by using 16 cameras and a large amount of diversity in deployment.We develop a new technique for superresolving binary imagery by incorporating finite-alphabet prior knowledge. We employ a message-passing based algorithm called two-dimensional distributed data detection (2D4) to estimate the object pixel likelihoods. We present a novel complexity-reduction technique that makes the algorithm suitable even for channels with support size as large as 5x5 object pixels. We compare the performance and complexity of 2D4 with that of IBP. In an imaging system with an optical blur spot matched to pixel size, and four 2x2 undersampled LR images, the reconstruction error for 2D4 is 300 times smaller than that for IBP at a signal-to-noise ratio of 38dB.We also present a transform-domain superresolution algorithm to efficiently incorporate sparsity as a form of prior knowledge. The prior knowledge that the object is sparse in some domain is incorporated in two ways: first we use the popular L1 norm as the regularization operator. Secondly we model wavelet coefficients of natural objects using generalized Gaussian densities. The model parameters are learned from a set of training objects and the regularization operator is derived from these parameters. We compare the results from our algorithms with an expectation-maximization (EM) algorithm for L1 norm minimization and also with the linear minimum mean squared error (LMMSE) estimator.

Made available in DSpace on 2015-03-26T13:51:49Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1551003 bytes, checksum: ef7a12dee1027c9dad410d80a2413fed (MD5) Previous issue date: 2009-02-18 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The objective of this work was to compare the bacterial diversity found in soils under eucalyptus with those found under native forest. Six areas belonging to Celulose Nipo-Brasileira - CENIBRA were studied; three of them were eucalyptus plantations and three were preserved native forests. They were located in two different projects of the company, the Crystal Lake and the Jacinto Lake, bearing two classes of soils, Latosol and Fluvic Neosol. Sampling was performed in March 2008 and bacterial diversity was assessed for the α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria, Actinobacteria and Firmicutes phyla. Denaturing Gradient Gel Electrophoresis (DGGE) was carried out for genetic diversity analysis and the resolved gel images were analyzed with the GELCOMPARII® software (Applied Maths, Inc - Texas USA). Shannon Weaver diversity indexes were calculated by means of the software Diversity of Species v. 2.0 (W.C Rodrigues - Lizaro Soft - Entomologists of Brazil - Brazil) The highest diversity indexes for total bacteria (Eubacteria), β-Proteobacteria, γ-Proteobacteria, and Actinobacteria was found in soils of native forests. Soils under eucalyptus forests displayed the highest diversity index for α- Proteobacteria and Firmicutes. The phylum α-Proteobacteria was the dominant one in Latosol and Neosol, both under eucalyptus and native forests. Diversity among Firmicutes and γ-Proteobacteria was also expressive; however, diversity of Actinobacteria and β-Proteobacteria was lowest in all areas studied. Diversity indexes averages among all phyla, when classes of soils were compared, were higher for Latosols, except for those of Firmicutes. The highest Eubacteria diversity index in soils under native forests as compared to those displayed under eucalyptus corroborates the hypothesis that plant coverage determines shifts in the microbial communities diversity. / Este trabalho teve como objetivo avaliar e comparar a diversidade bacteriana de solos sob plantio de eucalipto com a encontrada sob solos de mata nativa da região. O estudo abrangeu seis áreas da Empresa Celulose Nipo-Brasileira, sendo três áreas destinadas ao plantio de eucalipto e três áreas de mata nativa conservada, em dois projetos da empresa, o da Lagoa Cristal e o da Lagoa do Jacinto, em solos de duas classes, Latossolo e Neossolo flúvico. A amostragem foi realizada nas seis áreas em março de 2008 para a realização das análises de diversidade de bactérias pertencentes aos filos α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria, Actinobacteria e Firmicutes. A eletroforese em gel com gradiente desnaturante (DGGE), foi a técnica de escolha, sendo a análise da diversidade genética, com uso das imagens dos geis, realizada com o software GelComparII® (Applied Maths, Inc. - Texas USA). Para os cálculos do índice de diversidade de Shannon-Weaver foi utilizado o software Diversidade de Espécies v-2.0 (W. C. Rodrigues - Lizaro Soft - Entomologistas do Brasil - Brasil). No estudo da comunidade de bactérias totais (Eubacteria) e de β-Proteobacteria, γ-Proteobacteria e Actinobacteria, o maior índice de diversidade correspondeu a solos sob mata nativa. Para α-Proteobacteria e Firmicutes os maiores índices foram os encontrados para solos sob eucalipto. O filo α-Proteobacteria foi o caracterizado como o dominante em Latossolo e Neossolo, tanto nos sob eucalipto como nos sob mata nativa. A diversidade em Firmicutes e γ-Proteobacteria foi também expressiva, porém em Actinobacteria e β-Proteobacteria a diversidade foi menor em todas as áreas em estudo. As médias dos índices de diversidade de filos considerando as classes de solo foram maiores em Latossolo, excetuando-se a de Firmicutes, em que a maior diversidade foi em solo sob eucalipto. O maior índice de diversidade de Eubacteria em solos sob mata dos que nos solos sob eucalipto corroborou a afirmativa de que a cobertura vegetal determina alterações na diversidade da comunidade microbiana.