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2004 Conference object Unknown

An extended maximum likelihood approach for the robust blind separation of autocorrelated images from noisy mixtures
Gerace I., Cricco D., Tonazzini A.
In this paper we consider the problem of separating autocorrelated source images from linear mixtures with unknown coefficients, in presence of even significant noise. Assuming the statistical independence of the sources, we formulate the problem in a Bayesian estimation framework, and describe local correlation within the individual source images through the use of suitable Gibbs priors, accounting also for well-behaved edges in the images. Based on an extension of the Maximum Likelihood approach to ICA, we derive an algorithm for recovering the mixing matrix that makes the estimated sources fit the known properties of the original sources. The preliminary experimental results on synthetic mixtures showed that a significant robustness against noise, both stationary and non-stationary, can be achieved even by using generic autocorrelation models.Source: ICA 2004 - Independent Component Analysis and Blind Signal Separation: Fifth International Conference, pp. 954–961, Granada, Spain, 22-24 September

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2004 Article Unknown

Modeling SAR images with a generalization of the rayleigh distribution
Kuruoglu E. E., Zerubia J.
Synthetic aperture radar (SAR) imagery has found important applications due to its clear advantages over optical satellite imagery one of them being able to operate in various weather conditions. However, due to the physics of the radar imaging process, SAR images contain unwanted artifacts in the form of a granular look which is called speckle. The assumptions of the classical SAR image generation model lead to a Rayleigh distribution model for the histogram of the SAR image. However, some experimental data such as images of urban areas show im­pulsive characteristics that correspond to underlying heavy­tailed distributions, which are clearly non­Rayleigh. Some alternative distributions have been suggested such as the Weibull, log­normal, and the k­distribution which had success in varying degrees de­pending on the application. Recently, an alternative model namely the ­stable distribution has been suggested for modeling radar clutter. In this paper, we show that the amplitude distribution of the complex wave, the real and the imaginery components of which are assumed to be distributed by the ­stable distribution, is a generalization of the Rayleigh distribution. We demonstrate that the amplitude distribution is a mixture of Rayleighs as is the k ­distribution in accordance with earlier work on modeling SAR images which showed that almost all successful SAR image models could be expressed as mixtures of Rayleighs. We also present parameter estimation techniques based on negative order moments for the new model. Finally, we test the performance of the model on urban images and compare with other models such as Rayleigh, Weibull, and the k­ distribution.Source: IEEE transactions on image processing 13 (2004): 527–533. doi:10.1109/TIP.2003.818017
DOI: 10.1109/TIP.2003.818017

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2004 Article Unknown

Statistical analysis of IR thermographic sequences by PCA
S. Marinetti, E. Grinzato, P. G. Bison, E. Bozzi, M. Chimenti, G. Pieri, O. Salvetti
Automatic processing of IR sequences is a desirable target in Thermal Non Destructive Evaluation (TNDE) of materials. Unfortunately this task is made difficult by the presence of many undesired signals that corrupt the useful information detected by the IR camera. In this paper the Principal Component Analysis (PCA) is used to process IR image sequences to extract features and reduce redundancy by projecting the original data onto a system of orthogonal components. As a thermographic sequence contains information both in space and time, the way of applying PCA to these data cannot be straightforwardly borrowed from typical applications of PCA where the information is mainly spatial (e.g. Remote Sensing, Face Recognition). This peculiarity has been analysed and the results are reported. Finally, in addition to the use of PCA as an unsupervised method, its use in a 'learning and measuring' configuration is considered.Source: Infrared physics & technology 46 (2004): 85–91. doi:10.1016/j.infrared.2004.03.012
DOI: 10.1016/j.infrared.2004.03.012

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2004 Article Open Access OPEN

An alpha-stable approach to the study of the P(D) distribution of unresolved point sources in CMB sky maps
Herranz D., Kuruoglu E. E., Toffolatti L.
We present a new approach to the statistical study and modelling of point source counts in astronomical images. The approach is based on the theory of alpha-stable distributions. We show that the non-Gaussian distribution of the intensity fluctuations produced by a generic point source population -- whose number counts follow a simple power law -- belongs to the alpha-stable family of distributions. Even if source counts do not follow a simple power law, we show that the alpha-stable model is still useful in many astrophysical scenarios. With the alpha-stable model it is possible to totally describe the non-Gaussian distribution with a few parameters which are closely related to the parameters describing the source counts, instead of an infinite number of moments. Using statistical tools available in the signal processing literature, we show how to estimate these parameters in an easy and fast way. Then we apply the method to Cosmic Microwave Background (CMB) observations where point sources appear as superimposed to the cosmological signal as well as the instrumental noise, and propose a method to statistically disentangle these contributions. In the case of the Planck mission, our technique is able to determine the parameters of the dominant point source populations with relative errors 5% for the 30 GHz and 857 GHz channels. The formalism and methods presented here can be useful also for experiments in other frequency ranges such as X-rays or radio Astronomy.Source: Astronomy & astrophysics (Print) 424 (2004): 1081–1096. doi:10.1051/0004-6361:20035858
DOI: 10.1051/0004-6361:20035858

See at: arXiv.org e-Print Archive Open Access | DOI Resolver | www.aanda.org | CNR People


2004 Article Unknown

A general automatic method for the analysis of NREM sleep microstructure
Barcaro U., Bonanni E., Maestri M., Murri L., Parrino L., Terzano M. G.
The NREM sleep EEG of 10 normal subjects was examined in order to recognize formal phasic events of sleep microstructure. The event identification was carried out following a three-step procedure: (1) computation of band-related descriptors derived from the EEG signal, (2) introduction of suitable thresholds and (3) application of simple logical principles, i.e. an exclusion principle and an overlapping principle.Source: Sleep medicine (Amsterdam. Print) 5 (2004): 567–576. doi:10.1016/j.sleep.2004.07.012
DOI: 10.1016/j.sleep.2004.07.012

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2004 Article Unknown

Foraging strategies of breeding seabirds studied by bird-borne data loggers
Benvenuti S., Dall'Antonia L.
Our research group has devised and manufactured a data logger which glued on the back of a bird, can detect and memorise the direction in which the bird is heading during a flight. Given the birds' constant cruising speed, the memorised data can be used to recon-struct the whole flight path. Subsequent versions of this direction recorder, equipped with new sensors (depth meter and flight sensor), were used to investigate the foraging behaviour of several species of breeding marine birds (Balearic shearwater, Brünnich's guillemot, com-mon guillemot, razorbill, black-legged kittiwake, Audouin's gull, northern gannet, blue-foot-ed booby). The data recorded at different colony sites allowed us to identify the birds' feed-ing grounds and record the most relevant events occurring in the foraging trips, including the duration of the trips, total flight time, number and duration of the stops where feeding actual-ly occurred, dive profiles and diving behaviour. Differences in the foraging strategies between sexes and between incubating and brooding birds were also investigated.Source: Memoirs of National Institute of Polar Research. Special issue 58 (2004): 110–117.

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2004 Conference object Unknown

A 2-dimensional Wavelet based approach to recognise defects in C-scan maps
Bozzi E., Cavaccini G., Chimenti M., Di Bono M. G., Salvetti O.
An image processing procedure is proposed to detect porosity defects in composite materials, analyzing C-scan images obtained by ultrasound inspection techniques. An image described by a set of features is analyzed in order to evaluate its similarity with a reference set. A 2D wavelet transform is applied to the input image and then a feature extraction based on statistics of the detail images produced by the transform itself is performed. The Principal Component Analysis technique (PCA) is then applied in order to map input features into an output plane maximizing data variance. Finally the image is classified considering the distance between points in the PCA plane. This procedure is also applied for the analysis of a single image. Preliminary results on simulation images and real C-scan maps, show that the procedure is able to detect defects.Source: The 7h International Conference on Pattern Recognition and Image Analysis, pp. 627–630, St. Petersburg, 18-23 October 2004

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2004 Conference object Unknown

Astrophysical image denoising using bivariate isotropic cauchy distributions in the undecimated wavelet domain
Achim A., Herranz D., Kuruoglu E. E.
Within the framework of wavelet analysis, we describe a novel technique for removing noise from astrophysical im- ages. We design a Bayesian estimator, which relies on a particular member of the family of isotropic ®-stable dis- tributions, namely the bivariate Cauchy density. Using the bivariate Cauchy model we develop a noise-removal pro- cessor that takes into account the interscale dependencies of wavelet coe±cients. We show through simulations that our proposed technique outperforms existing methods both visually and in terms of root mean squared error.Source: IEEE International Conference on Image Processing (ICIP), pp. 1225–1228, Singapore, 24-27 October 2004

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2004 Conference object Unknown

Bayesian separation of independent sources in astrophysical radiation maps using MCMC
Kuruoglu E. E., Comparetti P. M.
In this work, we present a novel approach to the recovery of independent sources of radiations in sky maps. The work is motivated by the need to resolve CMB and other specific sources of radiation from a mixture of sources in the observations that are to be made by the Planck satellite after its launch in 2007. In particular, we present a numerical approach for Bayesian estimation namely Markov Chain Monte Carlo (MCMC) that exploits available prior information about radiation sources and hence differs from most of other work in the literature which are generally blind. MCMC provides large flexibility in modelling the problem and avoids analytical difficulties by resorting to numerical techniques. Results demonstrate the success and the flexibility of the approach.Source: PHYSTAT. Statistical Problems in Particle Physics, Astrophysics, and Cosmology, pp. 321–323, Stanford, USA, 8th-11th, September 2003

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2004 Conference object Unknown

Joint blind separation and restoration of mixed degraded images for document analysis
Tonazzini A., Gerace I., Cricco F.
We consider the problem of extracting clean images from noisy mixtures of images degraded by blur operators. This special case of source separation arises, for instance, when analyzing document images showing bleed-through or show-through. We propose to jointly perform demixing and deblurring by augmenting blind source separation with a step of image restoration. Within the ICA approach, i.e. assuming the statistical independence of the sources, we adopt a Bayesian formulation were the priors on the ideal images are given in the form of MRF, and a MAP estimation is employed for the joint recovery of both the mixing matrix and the images. We show that taking into account for the blur model and for a proper image model improves the separation process and makes it more robust against noise. Preliminary results on synthetic examples of documents exhibiting bleed-through are provided, considering edge-preserving priors that are suitable to describe text images.Source: IEEE International Conference on Image Processing, pp. 311–314, Singapore, October 24-27, 2004

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2004 Conference object Unknown

Separation of dependent sources in astrophysical radiation maps using second order statistics
Bedini L., Bottini S., Herranz D., Kuruoglu E. E., Salerno E., Tonazzini A.
This paper proposes a semi-blind approach for the separation of sources that are not totally uncorrelated. Up to now, all work on separation of components in astrophysical maps have assumed statistically independent sources. In this work, we attempt to perform a dependent component analysis of astrophysical sources and we propose a semi-blind algorithm which provides separation using second-order statistics only.Source: Astronomical Data Analysis, pp. 1–9, Sant' Agata dei due Golfi, 28 April - 1 May 2004

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2004 Conference object Unknown

The elements of information technology for cytological specimen image analysis: taxonomy and factor analysis
Vorobjev I. A., Gurevich I., Mekhedov I. S., Nefyodov A., Salvetti O., Trykova A. A., Harazishvili D. V.
The investigations are described concerning design of automated systems of hematopoietic tumors diagnostics. The elements of information technology for automation of diagnostic analysis of cytological specimen, such as taxonomy and factor analysis are considered. The results of testing the stability of the used methods for the larger size of learning sample are given. The usefulness of the proposed methods for discriminating patients with different types of tumor is empirically justified.Source: 7th International Conference on Pattern Recognition and Image Analysis: New Information Technologies, pp. 966–969, St. Petersburg, 18-23 October 2004

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2004 Conference object Unknown

Use of the BLOB analysis in the development of a new procedure for the automatic count of granulocytes migrating through micropore filters in chemotactic boyden chamber
Azzarà A., Chimenti M., Carulli G., Galimberti S., Fazzi R., Andreazzoli F., Petrini M.
In this paper we describe a completely new image processing procedure for an automatic assessment of granulocyte motility in micropore filters.Source: VIII Congress of the Italian Society of Experimental Hematology, pp. 122–123, Pavia, Italy, 14-16 September 2004

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2004 Conference object Unknown

Using alpha-stable distributions to model the P(D) distribution of point sources in CMB sky maps
Herranz D., Kuruoglu E. E., Toffolatti L.
We present a new approach to the statistical modelling of point source counts in astronomical images. The approach is based on the theory of alpha-stable distributions. We show that the distribution of the intensity fluctuations produced by a generic point source population belongs to the alpha-stable family of distributions. With the alpha-stable model it is possible to totally describe the non-Gaussian distribution with a few parameters which are closely related to the parameters describing the source counts. Using statistical tools available in the signal processing literature, we show how to estimate these parameters in an easy and fast way. Then we apply the method to Cosmic Microwave Background (CMB) observations where point sources appear as superimposed to the cosmological signal as well as the instrumental noise, and propose a method to statistically disentangle these contributions. In the case of the Planck mission, our technique is able to determine the parameters of the dominant point source populations with relative errors < %5 for the 30 GHz and 857 GHz channels. The formalism and methods presented here can be useful also for other experiments in other frequency ranges such as X-rays or radio Astronomy.Source: Conference on Statistical Problems in Particle Physics, Astrophysics and Cosmology, PHYSTAT, SLAC, TSnfaord, CA, USA, 8-11 September 2003

See at: www-conf.slac.stanford.edu | CNR People


2004 Report Unknown

A study for a portable IR sensor to detect the blood temperature during coronary bypass implantation
Mochi M., Giovanetti G., Francesconi R., Hartwig V., Landini L., Benassi A.
The objective of this research was to investigate the possibility of using an infrared prototype device for the detection of the blood temperature during a surgical operation for coronary bypass implantation. The correlation between the fluid temperature profile and the fluid flow rate was demonstrated. Currently, an expensive infrared (IR) camera placed in a corner of the operating room is used for the qualitative detection of these data, but a lot of problems arise regarding noise generated by external heat sources (medical staff, instrumentation...). The idea was to design a low cost portable device to be placed near the region of interest. Each blood vessel acts like a thermal wave emitter, so the amount of heat is proportional to the blood flow detected by the IR sensor. The first step in our research was the implementation of a coronary system model for predicting its operation and carrying out punctual and profile measurements. We chose a pyroelectric sensor for its high quality-cost ratio. Because this kind of sensor detects only a variable infrared source, we used an electromechanical chopper for modulating the radiation. It consists of an electronic shutter whose opening speed is controlled by an astable multivibrator. The output signal was analysed using a dedicated electronic circuit including a bandpass filter and an amplifier; then an acquisition board is employed for capturing and displaying the signal using a PC. The prototype assessment was made using a laboratory equipment. Further steps will concern in vivo measurements during surgical operation for coronary bypass implantation.

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2004 Report Unknown

Analisi dello Stato dell'Arte degli Algoritmi di Tracking e Motion Detection
Pieri G., Salvetti O.
The activity object of attention in this document regards in particular the development of algorithms of tracking and motion detection applied to infrared and visible spectrum images for surveillance and monitoring systems. Existing algorithms are studied for the location, the recognition and the automatic tracking of targets in motion, in conditions of partial masking, applied to infrared and visible video. The final goal will be the selection of candidate algorithms to be studied.

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2004 Report Unknown

Bleed-through removal from degraded documents using a color decorrelation method
Tonazzini A., Salerno E., Mochi M., Bedini L.
A color decorrelation strategy to improve the human or automatic readability of degraded documents is presented. The particular degradation that is considered here is bleed-through, that is, a pattern that interferes with the text to be read due to seeping of ink from the reverse side of the document. A simplified linear model for this degradation is introduced to permit the application of decorrelation techniques to the RGB components of the color data images, and to compare this strategy to the independent component analysis approach. Some examples from an extensive experimentation with real ancient documents are described, and the possibility to further improve the restoration performance by using hyperspectral/multispectral data is envisaged.

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2004 Report Unknown

Camera per misure di pressione intraoculare
Bozzi E., Chimenti M.
Il lavoro descrive un dispositivo per l'esecuzione di misure tonometriche e di pressione interna. Il dispositivo è costituito da: una camera di supporto, in grado di alloggiare senza deformazioni cornee spiantate, dotata di un ingresso per l'inserimento di liquido e un'uscita per l'eliminazione di bolle d'aria; un misuratore di pressione per liquidi. L'attività di ricerca e sviluppo è stata svolta nell'ambito di un contratto con l'Istituto di Clinica Oculistica del Dipartimento di Neuroscienze dell'Università di Pisa.

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2004 Report Unknown

Edge-Preserving Permittivity Range Profile Reconstruction by a Genetic Algorithm
Salerno E., Genovesi S., Monorchio A., Manara G.
Reconstructing the permittivity range profile of a layered medium from bandlimited backscattered data always implies either higly unstable or oversmoothed results. To avoid this drawback, we introduce an edge-preserving regularization constraint with explicitly marked lines. The inverse scattering problem is solved by a genetic optimization algorithm.Source: pp.1–7, 2004

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2004 Report Unknown

Image denoising using bivariate alpha-stable distributions in the complex wavelet domain
Achim A., Kuruoglu E. E.
Recently, the dual-tree complex wavelet transform has been proposed as a novel analysis tool featuring near shift-invariance and improved directional selectivity compared to the standard wavelet transform. Within this framework, we describe a novel technique for removing noise from digital images. We design a bivariate maximum a posteriori (MAP) estimator, which relies on the family of isotropic alpha-stable distributions. Using this relatively new statistical model we are able to better capture the heavy-tailed nature of the data as well as the interscale dependencies of wavelet coefficients. We test our algorithm for the Cauchy case, in comparison with several recently published methods. The simulation results show that our proposed technique achieves state-of-the-art performance in terms of root mean squared error.Source: pp.1–10, 2004

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