Abstract. In digital image processing for remote sensing there is often a need to interpolate an image. Examples occur in scale magnification, image registration, geometric correction, etc. On the other hand, this image can be subject to several sources of degradation and it would be interesting to compensate also for this degradation in the interpolation process. Therefore, this article addresses the problem of combining interpolation and restoration in a single operation, thereby reducing the computational effort. This is done by means of two-dimensional, separable, Finite Impulse Response (FIR) filters. The ideal low pass FIR filter for interpolation is modified to account for the restoration process. The Modified Inverse Filter (MIF) and the Wiener Filter (WF) are used for this purpose. The proposed methods are applied to the interpolation-restoration of Landsat-5 Thematic Mapper data. The later process takes into account the degradation due to optics, detector and electronic filtering. A comparison with the Parametric Cubic Convolution (PCC) technique is made. The experimental results consist of interpolation-restoration processes of Landsat-5 Thematic Mapper images from 30 m to 15 m (scale magnification) but they could also be generalized to include deblurring on more general interpolation problems, like geometric correction
Cold cloud index (CCI) data derived from Meteosat infrared imagery are used to detect periodicities in convective activity in South America. The generally used Fourier transform (FT) cannot provide time-localized information but gives information on the average periodicity of oscillations over the entire time domain. As many events in the atmosphere are intermittent, wavelet transform (WT) is used to identify periodic events in CCI data. First, the Morlet WT is applied to different combinations of time series data of known periodicities to demonstrate the advantage of WT over FT. Later it is applied to CCI data over four 9 square areas between the latitudes 4.5N and 31.5S, and longitudes 54-45W. Near the equator periodic convective activities are observed to be more prominent in the boreal summer than in the austral summer. Between the latitudes 4.5 and 22.5S, 1-, 2-3-, approximately 5-, and 8-10-day oscillations are seen in the austral summer and seldom is any convective activity seen in the winter. In January semidiurnal variation of cloudiness is also observed for a few days. Farther south in the extratropics, approximately 10-and approximately 20-day periodic events, which refer to the baroclinic waves, are seen more prominently in the austral autumn and winter, and 1-and approximately 5-day oscillations are seen in the summer, perhaps due to convective cloudiness.
RESUMOForam estudados os fenômenos meteorológicos que ocorrem na Amazônia Central (Manaus) utilizando-se um conjunto de imagens de satélites, com o objetivo de identificar as oscilações que mais contribuem para a variabilidade da cobertura de nuvens, e verificar se há modificações nestas oscilações em anos de El Niño e La Niña. O ciclo anual e o ciclo semi-anual são os principais responsáveis pela variabilidade da cobertura de nuvens altas na região. As oscilações interanuais associadas aos fenômenos El Niño/La Niña também contribuem fortemente para a variabilidade total da cobertura de nuvens altas. As oscilações intra-sazonais e interdiurnas apresentam uma variabilidade menor. Estendendo-se a análise para uma região compreendida de 1,5°S a 6ºS e 68ºW a 54ºW, centrados em Manaus, observa-se que os períodos de 60, 45 e 30 dias possuem maior porcentagem de potência a leste de Manaus; o período de 20 dias possui maior porcentagem de potência no centro (próximo de Manaus); e os períodos de 8, 6 e 4 dias possuem maior porcentagem de potência a oeste de Manaus. As frentes frias que alcançam a janela de 10º de longitude e 2,5º de latitude centrada em Manaus, modulam de alguma forma a atividade convectiva na região de Manaus atuando como uma forçante das oscilações interdiurnas (47% dos casos), das oscilações intra-sazonais, (15%) e das oscilações de 55 a 65 dias (13%). Convém ressaltar que não necessariamente as frentes frias causaram as oscilações. As frentes podem favorecer ou induzir a convecção no local. PALAVRAS-CHAVEOscilações, Cobertura de nuvens, Convecção, Amazônia Central. Study of the variability of high cloud covering over central Amazon region ABSTRACT The meteorological phenomena that occur in the Central Amazonia (Manaus) are studied from ISCCP-C1 Satellite-based data. The oscillations that contribute more significantly to the cloud cover variability and its relation to El Niño and La Niña events case identified. The annual and semi-annual oscillation times scales are the main responsible for the variability of the high cloud cover over Manaus. The inter-annual oscillations associated with El Niño and La Niña events also contribute significantly to the total variability of the high cloud cover, while intraseasonal and day-to-day oscillations show a reduced contribution. However, the intraseasonal and day-to-day oscillations
Neural networks were used to predict the anomalies of the time series of monthly rainfall of the Northeastern Region of Brazil. The forecasts made using a feedforward network with backpropagation algorithm from the original data were not satisfactoiy. We have therefore tried to combine two advanced methods, Wavelet Transform and Neural networks. Three more types of neural networks were used. The selected neural networks include the Time Delay Neural Networks (TDNN), Radial Basis Functions (RBF) network and Neural Network Adaptive Wavelet. All networks were implemented in neural network simulator SNNS . The Neural Network Adaptive Wavelet was implemented by changing the standard sigmoidal nonlinearities to wavelet nonlinearities in the neurons. We compare the results obtained with unfiltered and filtered data. Using data obtained by filtering the wavelet transform coefficients significantly improved the results for all networks. The combination of TDNN with wavelet filtered data gave the best results.
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