1,721,061 research outputs found
A Study of the Relationships Between the Real Scene Statistics and Those of the Backscattered Signal
No full textPopular mathematical description of natural landscapes rely
upon fractal geometry and a peculiar parameter of the model is the Hurst coefficient HX, which rules the correlation properties of the real scene.
The random process modelling the remotely collected data may preserve the fractal behavior of the original scene and its second-order statistics is then characterized by a Hurst number HY . However, HY = HX is only one of the possibilities arising from the mapping real scene → collected data. The relationships between the two Hurst parameters, hence between the second-order properties of the correspondent random processes, are investigated in the simplified scenario where the above mapping is a zeromemory nonlinearity. The obtained results improve and corroborate the work of [2]
Interplay between detection strategies and stochastic resonance properties
Full text linkWe discuss how to exploit stochastic resonance with the methods of statistical theory of decisions. To do so, we evaluate two detection strategies: escape time analysis and strobing. For a standard quartic bistable system with a periodic drive and disturbed by noise, we show that the detection strategies and the physics of the double well are connected, inasmuch as one (the strobing strategy) is based on synchronization, while the other (escape time analysis) is determined by the possibility to accumulate energy in the oscillations. The analysis of the escape times best performs at the frequency of the geometric resonance, while strobing shows a peak of the performances at a special noise level predicted by the stochastic resonance theory. We surmise that the detection properties of the quartic potential are generic for overdamped and underdamped systems, in that the physical nature of resonance decides the competition (in terms of performances) between different detection strategies
Escape time characterization of pendular Fabry-Perot
No full textIn a pendular Fabry-Perot interferometer the system placed inside one of the minimum of the optomechanical potential undergoes an escape if it crosses the point of sudden change of reflectivity near the top of the potential well. We demonstrate that the loss of information that occurs retaining only the sequence of escapes, rather than the full trajectory, is mild if suitable signal processing techniques are applied to reveal the noise intensity or the presence of a coherent signal
Correlation Properties of Signals Backscattered from Fractal Profiles
No full textA successful mathematical description of natural landscapes relies upon a class of random processes known as fractional Brownian motions (fBms), which may exhibit correlation with long-range dependence (LRD). In remote sensing applications, the sensor observes a certain real scene B and records data I for successive signal processing tasks. Assuming that B is modeled as an fBm, does the recorded signal I preserve the LRD character of B? More in general, can we relate the Hurst coefficient (an index of LRD) of the real scene to that of the recorded data? We address the problem in a simplified setup in which the data are related to (the slope of) the original scene through a zero-memory mapping. A mathematical framework is presented in which the above questions can be answered in the asymptotic regime of infinite data size. The effect of the finite sample size is also investigated. The mathematical model is also validated by real data, which are collected by a synthetic aperture radar that is mounted onboard of ERS-1/2 satellites
A Class of Cloud Detection Algorithms Based on a MAP-MRF Approach in Space and Time
No full textA recurrent concern in cloud detection approaches is the high misclassification rate for pixels close to cloud edges. We tackle this problem by introducing a novel penalty term within the classical maximum a posteriori probability-Markov random field (MAP-MRF) approach. To improve the classification rate, such term, for which we suggest two different functional forms, accounts for the predictable motion of cloud volumes across images. Two mass tracking techniques are proposed. The first one is an effective and efficient implementation of the probability hypothesis density (PHD) filter, which is based on Gaussian mixtures (GMs) and relies on finite set statistics (FISST). The second one is a region matching procedure based on a maximum cross-correlation (MCC) that is characterized by low computational load. Through extensive tests on simulated images and real data, acquired by the SEVIRI sensor, both methods show a clear performance gain in comparison with classical spatial MRF-based algorithms
On the Influence of the Surface Fractal Dimension on the IFSAR Baseline Decorrelation
No full textCoherence is the key factor in Synthetic Aperture Radar Interferometry. We study the baseline decorrelation due to antenna spatial diversity in order to take into account the effect of the surface statistic roughness in a more general case. As a model of surface roughness we use the fractional Brownian motio
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