881 resultados para Radar image
Resumo:
Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scienti c activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy e ciency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to nd the optimum hardware for a cost-e ective execution.
Resumo:
Purpose: Many countries used the PGMI (P=perfect, G=good, M=moderate, I=inadequate) classification system for assessing the quality of mammograms. Limits inherent to the subjectivity of this classification have been shown. Prior to introducing this system in Switzerland, we wanted to better understand the origin of this subjectivity in order to minimize it. Our study aimed at identifying the main determinants of the variability of the PGMI system and which criteria are the most subjected to subjectivity. Methods and Materials: A focus group composed of 2 experienced radiographers and 2 radiologists specified each PGMI criterion. Ten raters (6 radiographers and 4 radiologists) evaluated twice a panel of 40 randomly selected mammograms (20 analogic and 20 digital) according to these specified PGMI criteria. The PGMI classification was assessed and the intra- and inter-rater reliability was tested for each professional group (radiographer vs radiologist), image technology (analogic vs digital) and PGMI criterion. Results: Some 3,200 images were assessed. The intra-rater reliability appears to be weak, particularly in respect to inter-rater variability. Subjectivity appears to be largely independent of the professional group and image technology. Aspects of the PGMI classification criteria most subjected to variability were identified. Conclusion: Post-test discussions enabled to specify more precisely some criteria. This should reduce subjectivity when applying the PGMI classification system. A concomitant, important effort in training radiographers is also necessary.
Resumo:
The aim of this study was to evaluate and compare organ doses delivered to patients in wrist and petrous bone examinations using a multislice spiral computed tomography (CT) and a C-arm cone-beam CT equipped with a flat-panel detector (XperCT). For this purpose, doses to the target organ, i.e. wrist or petrous bone, together with those to the most radiosensitive nearby organs, i.e. thyroid and eye lens, were measured and compared. Furthermore, image quality was compared for both imaging systems and different acquisition modes using a Catphan phantom. Results show that both systems guarantee adequate accuracy for diagnostic purposes for wrist and petrous bone examinations. Compared with the CT scanner, the XperCT system slightly reduces the dose to target organs and shortens the overall duration of the wrist examination. In addition, using the XperCT enables a reduction of the dose to the eye lens during head scans (skull base and ear examinations).
Resumo:
During adolescence, nutrition needs are high; however the literature shows that few adolescents are following standardized nutritional requirements. A few weeks before an intervention about nutrition to high school adolescents in Lausanne, they were invited to fill in a self-reported questionnaire about their nutrition modes and habits, and their self-image satisfaction (N = 198). Results show that only 5% of youth are eating 5 fruits and vegetables per day and only 29% 3 to 5 dairy products. 21% of female and 6% of boys are not satisfied about their self-image, and those exhibiting a poor self-image tend to adopt health compromising eating patterns in a higher proportion. During adolescence it is important not only to investigate the nutritional habits but also one's self image.
Resumo:
Em virtude da crescente demanda mundial por alimentos, um monitoramento eficaz e em larga escala da umidade do solo constitui fator de grande importância para a previsão de safras. Este trabalho teve por objetivo apresentar uma técnica para o cálculo do teor de água no solo, utilizando modelos preditivos de umidade do solo, baseados em dados de radar de abertura sintética (SAR). Foram utilizados dados do SAR a bordo do JERS-1 ("Japanese Earth Resources Satellite") e dois modelos empíricos. O primeiro relaciona o coeficiente de retroespalhamento com a permissividade complexa (modelo de Dubois), e o segundo relaciona a permissividade complexa com o teor de água do solo e algumas de suas características físico-hídricas, tais como percentagem de areia e argila (modelo de Hallikainen). Inicialmente, os dados do SAR/JERS-1 foram calibrados e, por meio do modelo de Dubois, foram calculados os valores de permissividade complexa. Para tanto, foi necessário inserir níveis estimados de rugosidade do solo. A partir destes resultados, utilizou-se o modelo de Hallikainen para calcular a umidade volumétrica. A análise geral dos resultados indica que a técnica de estimação de umidade do solo a partir de imagens de radar de abertura sintética, utilizada neste estudo, mostrou-se física e matematicamente exeqüível. No entanto, apresentou uma precisão moderada, não sendo ainda recomendada para o uso operacional no mapeamento de umidade do solo. A análise dos resultados revelou também que a precisão dos dados é bastante influenciada pela precisão dos valores de rugosidade introduzidos.
Resumo:
In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.
Resumo:
Foram estudados nove perfis ao longo de uma toposseqüência sobre os sedimentos do Grupo Barreiras, na Fazenda Rio Negro, município de Entre Rios (BA), utilizando a prospecção eletromagnética por meio do Radar Penetrante no Solo - "Ground-penetrating radar - GPR", objetivando analisar a utilização dessa ferramenta na aquisição de informações sobre as feições que ocorrem no solo, mediante a comparação entre os radargramas obtidos e a descrição pedológica. O equipamento utilizado foi um Geophysical Survey System modelo GPR SR system-2, com antena de 80 MHz. A análise radargramétrica confirmou o aparecimento dos fragipãs e duripãs em profundidade, que ocorrem sempre acompanhados de um processo de transformação dos solos do tipo Latossolo Amarelo e Argissolo Amarelo em Espodossolo. Os padrões de reflexão mostram claramente os domínios dos solos argilosos e dos solos arenosos, com e sem a presença dos horizontes endurecidos.