The growing of mobile communication market is attracting the prospects of "cyber-criminals&q... more The growing of mobile communication market is attracting the prospects of "cyber-criminals" to eavesdrop personal and financial data through mobile devices. Typically, such devices do not have enough hardware resources to provide a secure environment against phishing attacks, spywares, malwares, identity theft and so on. In this paper, we propose a Telco architecture designed to prevent some mobile attacks that
IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004, 2004
... Paolo Addesso, Stefano Marano and Rocco Restaino Dipartimento di Ingegneria dell&... more ... Paolo Addesso, Stefano Marano and Rocco Restaino Dipartimento di Ingegneria dell'Informazione e Ingegneria Elettrica Universit`a degli Studi di Salerno via Ponte don Melillo, I-84084 Fisciano (SA), Italy Telephone: (+39) 089 ... [6] G. Franceschetti, M. Migliaccio, D. Riccio and G ...
Popular mathematical description of natural landscapes rely upon fractal geometry and a peculiar ... more Popular 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
The implementation of risk maps for fire hazard management is dealt with. We assume that a binary... more The implementation of risk maps for fire hazard management is dealt with. We assume that a binary-classified image is obtained either from a simulated lattice or from a re- motely sensed image, using appropriate classification procedures. Starting from that, different risk indices are considered and the pertinent risk maps are implemented, using two idealized model of fire propagation, one deterministic and another random. I. INTRODUCTION There is no need to stress the impact that fires may have on our everyday life, on the safety of the global ecosystem, not to mention the economic/social costs. Consequently, enormous is the interest in the early detection, path prediction and, more in general, in fire risk managing. In these respects, remotely sensed images - best if integrated with field informations and other on-situ-collected data - play an important role as they provide a mean for large-area monitor and control. The scientific literature addressing the problem is huge, reflecting the relevant progresses made in the last decades, see for instance (1). Here we are interested in a specific aspect of the above issue, namely in the implementation of fire risk maps amounting to assigning a cost index to each region (assume a single pixel) of a surveyed area (identified with the whole remotely sensed image). The general aim is to provide a quantitative measure of how much a fire that is detected in a given point is potentially dangerous for the surrounding area, with the practical goal of supporting human decisions about time and modality of actions to be taken against fire
IEEE Transactions on Geoscience and Remote Sensing, 2015
ABSTRACT Many powerful pansharpening approaches exploit the functional relation between the fusio... more ABSTRACT Many powerful pansharpening approaches exploit the functional relation between the fusion of PANchromatic (PAN) and MultiSpectral (MS) images. To this purpose, the modulation transfer function of the MS sensor is typically used, being easily approximated as a Gaussian filter whose analytic expression is fully specified by the sensor gain at the Nyquist frequency. However, this characterization is often inadequate in practice. In this paper, we develop an algorithm for estimating the relation between PAN and MS images directly from the available data through an efficient optimization procedure. The effectiveness of the approach is validated both on a reduced scale data set generated by degrading images acquired by the IKONOS sensor and on full-scale data consisting of images collected by the QuickBird sensor. In the first case, the proposed method achieves performances very similar to that of the algorithm that relies upon the full knowledge of the degrading filter. In the second, it is shown to outperform several very credited state-of-the-art approaches for the extraction of the details used in the current literature.
Abstract. In this paper we present a cloud detection algorithm exploit-ing both the spatial and t... more Abstract. In this paper we present a cloud detection algorithm exploit-ing both the spatial and the temporal correlation of cloudy images. A region matching technique for cloud motion estimation is embodied into a MAP-MRF framework through a penalty term. We test our proposal ...
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
ABSTRACT Pansharpening algorithms aim to enhance low resolution multi-spectral images by means of... more ABSTRACT Pansharpening algorithms aim to enhance low resolution multi-spectral images by means of high resolution panchromatic ones. Several approaches are based on the MultiResolution Analysis (MRA) achieved through the pyramidal decomposition of images. We focus here on the implementation based on Morphological Filters (MF) that are optimized through Genetic Algorithms (GA). The effectiveness of this algorithm is compared with other techniques, among which those based on Wavelet operators, through several quality indices on two different real scenarios.
ABSTRACT The application of sparse representation (SR) theory to the fusion of multispectral (MS)... more ABSTRACT The application of sparse representation (SR) theory to the fusion of multispectral (MS) and panchromatic images is giving a large impulse to this topic, which is recast as a signal reconstruction problem from a reduced number of measurements. This letter presents an effective implementation of this technique, in which the application of SR is limited to the estimation of missing details that are injected in the available MS image to enhance its spatial features. We propose an algorithm exploiting the details self-similarity through the scales and compare it with classical and recent pansharpening methods, both at reduced and full resolution. Two different data sets, acquired by the WorldView-2 and IKONOS sensors, are employed for validation, achieving remarkable results in terms of spectral and spatial quality of the fused product.
IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004, 2004
... Paolo Addesso, Maurizio Longo and Rocco Restaino Dipartimento di Ingegneria dell'Inf... more ... Paolo Addesso, Maurizio Longo and Rocco Restaino Dipartimento di Ingegneria dell'Informazione e Ingegneria Elettrica Universit`a degli Studi di Salerno via Ponte don Melillo, I-84084 Fisciano (SA), Italy Telephone: (+39) 089 ... [4] Franceschetti, G., A. Iodice, M. Migliaccio and D ...
ABSTRACT Accurate estimation of physical quantities depends on the availability of High Resolutio... more ABSTRACT Accurate estimation of physical quantities depends on the availability of High Resolution (HR) observations of the Earth surface. However, due to the unavoidable tradeoff between spatial and time resolution, the acquisition instants of HR data hardly coincides with those required by the estimation algorithms. A possible solution consists in constructing a synthetic HR observation at a given time k by exploiting Low Resolution (LR) and HR data acquired at different instants. In this work we recast this issue as a smoothing problem, thus focusing on cases in which observations acquired both before and after time k are available. The proposed approach is validated on a region of interest for the IRRISAT irrigation management project in which the surface thermal inertia estimation, requiring multiple HR images at specific instants, constitute a key step.
Automatic genre classification of audio signals is an open challenge of pattern recognition. The ... more Automatic genre classification of audio signals is an open challenge of pattern recognition. The fractal nature of the music signals indicates the Hausdorff dimension as a distinguish feature for classifying audio tracks. However this key parameter cannot be unequivocally defined since it is not constant during the whole track, but it ranges in a wide set of values. The aim of this paper is to face the classification task by comparing the empirical distributions of the fractal dimensions recorded during each track. We show that this single feature allows to achieve very promising results, especially in view of designing more complex classifiers that combine it with other commonly used descriptors.
The estimation of the fractal dimension of certain functions with fractal behavior is addressed. ... more The estimation of the fractal dimension of certain functions with fractal behavior is addressed. We consider the morphologic covering- and the ML-based estimation algorithms which have been proposed in the literature, and compare their performances on quantized and possibly noise-corrupted data
The growing of mobile communication market is attracting the prospects of "cyber-criminals&q... more The growing of mobile communication market is attracting the prospects of "cyber-criminals" to eavesdrop personal and financial data through mobile devices. Typically, such devices do not have enough hardware resources to provide a secure environment against phishing attacks, spywares, malwares, identity theft and so on. In this paper, we propose a Telco architecture designed to prevent some mobile attacks that
IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004, 2004
... Paolo Addesso, Stefano Marano and Rocco Restaino Dipartimento di Ingegneria dell&... more ... Paolo Addesso, Stefano Marano and Rocco Restaino Dipartimento di Ingegneria dell'Informazione e Ingegneria Elettrica Universit`a degli Studi di Salerno via Ponte don Melillo, I-84084 Fisciano (SA), Italy Telephone: (+39) 089 ... [6] G. Franceschetti, M. Migliaccio, D. Riccio and G ...
Popular mathematical description of natural landscapes rely upon fractal geometry and a peculiar ... more Popular 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
The implementation of risk maps for fire hazard management is dealt with. We assume that a binary... more The implementation of risk maps for fire hazard management is dealt with. We assume that a binary-classified image is obtained either from a simulated lattice or from a re- motely sensed image, using appropriate classification procedures. Starting from that, different risk indices are considered and the pertinent risk maps are implemented, using two idealized model of fire propagation, one deterministic and another random. I. INTRODUCTION There is no need to stress the impact that fires may have on our everyday life, on the safety of the global ecosystem, not to mention the economic/social costs. Consequently, enormous is the interest in the early detection, path prediction and, more in general, in fire risk managing. In these respects, remotely sensed images - best if integrated with field informations and other on-situ-collected data - play an important role as they provide a mean for large-area monitor and control. The scientific literature addressing the problem is huge, reflecting the relevant progresses made in the last decades, see for instance (1). Here we are interested in a specific aspect of the above issue, namely in the implementation of fire risk maps amounting to assigning a cost index to each region (assume a single pixel) of a surveyed area (identified with the whole remotely sensed image). The general aim is to provide a quantitative measure of how much a fire that is detected in a given point is potentially dangerous for the surrounding area, with the practical goal of supporting human decisions about time and modality of actions to be taken against fire
IEEE Transactions on Geoscience and Remote Sensing, 2015
ABSTRACT Many powerful pansharpening approaches exploit the functional relation between the fusio... more ABSTRACT Many powerful pansharpening approaches exploit the functional relation between the fusion of PANchromatic (PAN) and MultiSpectral (MS) images. To this purpose, the modulation transfer function of the MS sensor is typically used, being easily approximated as a Gaussian filter whose analytic expression is fully specified by the sensor gain at the Nyquist frequency. However, this characterization is often inadequate in practice. In this paper, we develop an algorithm for estimating the relation between PAN and MS images directly from the available data through an efficient optimization procedure. The effectiveness of the approach is validated both on a reduced scale data set generated by degrading images acquired by the IKONOS sensor and on full-scale data consisting of images collected by the QuickBird sensor. In the first case, the proposed method achieves performances very similar to that of the algorithm that relies upon the full knowledge of the degrading filter. In the second, it is shown to outperform several very credited state-of-the-art approaches for the extraction of the details used in the current literature.
Abstract. In this paper we present a cloud detection algorithm exploit-ing both the spatial and t... more Abstract. In this paper we present a cloud detection algorithm exploit-ing both the spatial and the temporal correlation of cloudy images. A region matching technique for cloud motion estimation is embodied into a MAP-MRF framework through a penalty term. We test our proposal ...
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
ABSTRACT Pansharpening algorithms aim to enhance low resolution multi-spectral images by means of... more ABSTRACT Pansharpening algorithms aim to enhance low resolution multi-spectral images by means of high resolution panchromatic ones. Several approaches are based on the MultiResolution Analysis (MRA) achieved through the pyramidal decomposition of images. We focus here on the implementation based on Morphological Filters (MF) that are optimized through Genetic Algorithms (GA). The effectiveness of this algorithm is compared with other techniques, among which those based on Wavelet operators, through several quality indices on two different real scenarios.
ABSTRACT The application of sparse representation (SR) theory to the fusion of multispectral (MS)... more ABSTRACT The application of sparse representation (SR) theory to the fusion of multispectral (MS) and panchromatic images is giving a large impulse to this topic, which is recast as a signal reconstruction problem from a reduced number of measurements. This letter presents an effective implementation of this technique, in which the application of SR is limited to the estimation of missing details that are injected in the available MS image to enhance its spatial features. We propose an algorithm exploiting the details self-similarity through the scales and compare it with classical and recent pansharpening methods, both at reduced and full resolution. Two different data sets, acquired by the WorldView-2 and IKONOS sensors, are employed for validation, achieving remarkable results in terms of spectral and spatial quality of the fused product.
IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004, 2004
... Paolo Addesso, Maurizio Longo and Rocco Restaino Dipartimento di Ingegneria dell'Inf... more ... Paolo Addesso, Maurizio Longo and Rocco Restaino Dipartimento di Ingegneria dell'Informazione e Ingegneria Elettrica Universit`a degli Studi di Salerno via Ponte don Melillo, I-84084 Fisciano (SA), Italy Telephone: (+39) 089 ... [4] Franceschetti, G., A. Iodice, M. Migliaccio and D ...
ABSTRACT Accurate estimation of physical quantities depends on the availability of High Resolutio... more ABSTRACT Accurate estimation of physical quantities depends on the availability of High Resolution (HR) observations of the Earth surface. However, due to the unavoidable tradeoff between spatial and time resolution, the acquisition instants of HR data hardly coincides with those required by the estimation algorithms. A possible solution consists in constructing a synthetic HR observation at a given time k by exploiting Low Resolution (LR) and HR data acquired at different instants. In this work we recast this issue as a smoothing problem, thus focusing on cases in which observations acquired both before and after time k are available. The proposed approach is validated on a region of interest for the IRRISAT irrigation management project in which the surface thermal inertia estimation, requiring multiple HR images at specific instants, constitute a key step.
Automatic genre classification of audio signals is an open challenge of pattern recognition. The ... more Automatic genre classification of audio signals is an open challenge of pattern recognition. The fractal nature of the music signals indicates the Hausdorff dimension as a distinguish feature for classifying audio tracks. However this key parameter cannot be unequivocally defined since it is not constant during the whole track, but it ranges in a wide set of values. The aim of this paper is to face the classification task by comparing the empirical distributions of the fractal dimensions recorded during each track. We show that this single feature allows to achieve very promising results, especially in view of designing more complex classifiers that combine it with other commonly used descriptors.
The estimation of the fractal dimension of certain functions with fractal behavior is addressed. ... more The estimation of the fractal dimension of certain functions with fractal behavior is addressed. We consider the morphologic covering- and the ML-based estimation algorithms which have been proposed in the literature, and compare their performances on quantized and possibly noise-corrupted data
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Papers by Rocco Restaino