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The existence of long-lived electronic states is a remarkable property of two-electron atoms. Such states can be addressed and manipulated with ultranarrow lasers, allowing for the investigation of new phenomena in which multiple degrees of freedom are involved as well as for the realization of new quantum simulation and information schemes.

Identification of the source that has generated a digital content is considered one of the main open issues in multimedia forensics community. The extraction of photo-response non-uniformity (PRNU) noise has been so far indicated as a mean to identify sensor fingerprint. Such a fingerprint can be estimated from multiple images taken by the same camera by means of a denoising filtering operation. This paper presents an analysis of the performances of different denoising filters based on diverse noise models when applied for digital camera tracking. In particular, a digital filter, based on a signal-dependent noise model, is introduced and compared with others commonly adopted for this purpose. A theoretical framework and experimental results are provided and discussed.

Recently, thanks to the diffusion of scanning devices and the availability of powerful 3D modeling software, as well as to the improvements in the automation of the image-based modeling approach, it is foreseen that 3D models will become more and more ubiquitous in several research fields. However, 3D models obtained by these technologies often are lacking for a suitable photorealistic appearance, due to the low quality generated texture, or to the complete absence of it. A post-processing texture mapping is often used to obtain highly realistic models, through an accurate manual alignment of the model and the related texture. In this work, we propose an automatic approach for mapping the texture on flat-like 3D models, in which the depth component is smaller compared to the object's height and width, such as in bass-relieves, coins, paintings or facades. The method relies on the evaluation from the model geometry of a depth map, used to align the texture image. The results show the effectiveness of the proposed method.

RAPSODI is a research project funded by the European Commission within the sixth framework program. The aim of the project is the development of a set of radiation detectors for three well defined applications based on Silicon Photo-Multipliers (SiPM), representing the state-of-the-art in single photon sensitive detectors. This paper focuses on the currently most advanced RAPSODI application, namely in-vivo real-time dosimetry in mammography.

Cultural heritage field can benefit from the image processing field in many ways. Several years of research accomplished at MICC and DET have led to the establishment of an integrated software for image processing of cultural heritage images. The tool is able to protect the digital reproductions of art works, by means of a powerful and robust watermarking technique, as well as it put at disposal some virtual restoration tools, able both to simulate the actual restoration that can be performed over the real art work or to process digital images in order to improve their appearance, or to highlight some features of interest for restorers and curators. In the following, such a tool is presented, as well as some results of its application.

This paper discusses research conducted by The Very Low Frequency (VLF) Group at Stanford University introducing them and a project called the High Frequency Active Auroral Research Program (HAARP). This project utilizes the latest oceanographic and ocean-engineering technologies for exciting applications to space physics and radio science research. Sponsors consist of the Air Force Research Laboratory (AFRL), the Naval Research Laboratory (NRL), and the Defense Advanced Research Projects Agency (DARPA). The program's facility is a high power transmitter located in Alaska, capable of broadcasting powerful VLF radio waves into the Earth's ionosphere. These waves propagate along the Earth's magnetic field lines to the system's geomagnetic conjugate point situated nominally 600 miles south of New Zealand in the southern Pacific Ocean. By studying the radio signals at this point, the VLF Group seeks to discover how energetic particles in the planet's radiation belts interact with very low frequency electromagnetic waves. This ambitious challenge of operating an autonomous, stationary, floating observation platform is known as the HAARP One-Hop Experiment - South Pacific Buoy.

In the last few years, the Cultural Heritage field has posed its attention over image processing techniques, in particular for the diagnostic of art works. Many different images of the same painting are taken, in different parts of the light spectrum; these different images have to be fused together, to get an augmented image showing much more details and information which are only visible in some sub-parts of the spectrum singularly. In this paper, we pose the attention over the compulsory step accomplished just before the "fusion" of such images, i.e. the registration step; in particular, we present an automatic registration technique, based on the computation of mutual information. By means of the registration, it is possible to exactly align the different images, which is the preliminary step to obtain a useful and correct augmented image. These techniques can be also applied to other areas, and in particular to remote sensing images.

A real time imaging device for extended radioactive sources based on monolithic and hybrid position sensitive silicon sensors has been developed by the SUCIMA (silicon ultra fast cameras for electron and /spl gamma/ sources in medical applications) collaboration. In the following, results obtained imaging /sup 90/Sr and /sup 144/Ce brachytherapy sources are presented. Large area silicon strip detectors, read out by low noise charge integrating chips, have been used to measure the dose depth curves and the sources profiles in tissue equivalent material (according to the prescription of the American Association of Physicist in Medicine Task Group No. 60). All the performed measurements are validated by qualified GafChromic films comparison.

In art diagnostics it is often needed to compare and integrate different sets of information, coming from different sources, and stored in different images. In order to successfully integrate these data, images corresponding to the same areas need to be registered, that is a geometrical transformation that aligns points in one picture with corresponding points in another picture needs to be found and applied. In this paper we present an automatic registration technique for multispectral images, based on the computation of mutual information. We applied this method to obtain RGB images from multispectral data, and derive a (undersampled) spectral signature per pixel of the painting.

The application of information technology in the field of cultural heritage content, is now widely diffused, and many different aspects are subject to a deep investigation. Among these this paper in particular analyses the activities carried on over the years at the Image Processing and Communications Laboratory (Laboratorio Comunicazioni ed Immagini - LCI) of the Department of Electronics and Telecommunications of the University of Florence with reference to fine arts images quality improvement and copyright protection. An overview of the European level activities carried out by the Lab is finally given.

The progress of electronic imaging has encouraged the development of new tools for cultural heritage applications. In this paper some software, ArtShop, is described that contains tools for artwork image restoration, developed over several years of research.

In the last few years, digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia data against unauthorized uses. In the field of image watermarking, research has been mainly focused on grey-scale image watermarking, whereas the extension to the color case is usually accomplished by marking the image luminance, or by processing each color channel separately. In this paper, a DCT domain technique expressly devised for watermarking of color images is presented, which exploits the characteristics of the human visual system and the correlation between the RGB image channels. Experimental results are presented to demonstrate the validity of the new approach with respect to algorithms operating on image luminance only.

Scene analysis with processing of multiple frames is considered for automatic recognition and tracking of moving objects. The importance of taking into account information about the objects in the design of flexible systems is emphasized. This goal is reached through an object-oriented approach to problem-solving. It is shown that abstract data type and inheritance relationship definitions over real-world entities can be efficiently used for object classification purposes. This has been verified in a traffic monitoring application. An efficient algorithmic solution that satisfies the real-time constraints of the problem is proposed. >

Digital techniques for image processing and automatic classification in remote-sensing applications are described. Some digital filters suitable for radar noise reduction are reviewed. A novel filtering algorithm for multiplicative noise rejection is then proposed. Some algorithms using the maximum-likelihood decision rule or the Euclidean distance are applied to preprocessed images for an automatic discrimination of agricultural crops. Microwave images obtained by means of synthetic aperture radars and collected during the European SAR 580 campaign are used to evaluate the performance of the filtering algorithms. Both single-band and two-band classification with a correct classification probability of over 95% were obtained. >

The authors study the performance of different dynamic window flow control mechanisms in an ISDN (integrated services digital network) environment. The network model assumed is simple but general enough to account for different network environments. Virtual circuits belonging to several throughput classes are considered, and delay-throughput and grade of service performance are evaluated for different flow control mechanisms. The effectiveness of the throttled window control in a multi-throughput-class environment is demonstrated. The use of priority in dynamic flow control is suggested and proved to be effective in increasing the overall network performance. >

In ATM networks, SMDS services can be provided through interworking units (IWU), which use virtual paths to interconnect to the connectionless servers (CLS). The goal of this paper is to present a mechanism to achieve an efficient bandwidth allocation on the VPs. The scheduling algorithm, implemented in the IWU, allows to reserve as small as possible bandwidth, according to the offered traffic characteristics and the QoS requirements. A simulation model has been used to analyze its performance. This multiple rate multiplexer can be simplified by using only two output transmission speeds. In addition, a "time-credit" mechanism is proposed to control the parameters of the two-rate multiplexer. >

In the field of video coding the issues of backward prediction and standards conversion have focused an increasing attention towards techniques for an effective estimation of the true interframe motion. The problem of restoration of motion vector-fields computed by means of a standard block matching algorithm is addressed. The restoration must be carried out carefully by exploiting both the spatial correlation of the vector-field, and the significance of the obtained vectors as measures of the reliability of the previous estimation step. A novel approach matching both the above requirements is presented. Based on the theory of vector-median filters an adaptive scheme is developed and results are discussed.

The use of traffic monitoring techniques based on image processing algorithms for supervising urban vehicle flows could be very useful. Classical inductive loops can only compute traffic density on a single lane but are unable to estimate, for example, the behaviour of the vehicle flow at a crossroad. In this paper a system that estimates the turning rates at an urban crossroad by processing the sequence of images taken by a videocamera is presented. Block matching motion estimation, segmentation, and moving object tracking techniques are used. The good results obtained are presented and their relation to the camera position is discussed.

This paper focuses on the possibilities offered by neural networks applied to multisensor image data processing. The great number of existing and planned instruments for Earth observation (satellites, sensors) highlights the need of specific techniques for processing, and, in particular, for merging, the large amount of data that will be available in future years. Moreover emphasis is given to the importance of fusing data acquired by sensors operating in different regions of the electromagnetic spectrum. Neural networks (NNs) are employed to perform fusion of TM data with SAR data in order to obtain a landcover classification of an agricultural area in the surroundings of Florence (Italy). Two different architectures of NN are presented and employed, the counterpropagation network and the Kohonen map; the results obtained in both cases are reported and discussed. >

In spite of their good filtering characteristics, the use of vector median filters is often limited by their high computational complexity. This article describes a fast algorithm which permits to considerably reduce the computational burden of the vector median filter based on 1-norm. The validity of the algorithm is demonstrated both by means of theoretical results and experimental tests. In particular, it is shown that the proposed technique permits, to obtain the filtering accuracy of vector medians based on the aggregate sum of distances at a computational complexity which is typical of filters based on reduced ordering.

The progress of digital electroencephalography gave rise to the problem of EEG data recording. In the paper a DPCM scheme for EEG signal compression is discussed. In particular the performance of a class of predictors based on recurrent neural networks is presented. The training strategy is accurately described and the results of a comparison with some other classical linear and static neural predictors are given. The proposed recurrent neural predictor demonstrates to be competitive with the others in offering good performance at a very low computational cost.

The peculiarities of digital map images are exploited to develop a watermarking algorithm which is robust against geometric distortions. Robustness against geometric attacks is achieved through text-based image normalization. First, text is extracted from the to-be-marked map, then text orientation and size are exploited to normalize the image geometry prior to watermark insertion. Watermarking is performed by means of any of the existing algorithms ensuring good robustness against image processing tools. At the decoder side, text is extracted again from the map and used to normalize image geometry. Owing to the robustness of text features with respect to common image manipulations, and to the likely spreading of text all across the digital map, the proposed system exhibits an excellent robustness, as is witnessed by the experimental results reported.

Progress in electronic imaging over the last years has encouraged the development of new tools for cultural heritage applications. In particular, the areas of painting preservation and restoration have attracted the interest of researchers working in the field of image processing. A virtual tool for painting restoration, which simulates the actual restoration carried out in the restoration laboratory, is presented; in particular, the proposed techniques allow the virtual recovery and filling of the areas of a painting which are damaged by lacunas.

This paper studies the applicability of watermarking techniques to remote sensing imagery. An overview of watermarking is given, and the requirements, imposed by the remote sensing scenario on watermarking techniques, are discussed. As an example, the effect of watermarking on image classification is analyzed.

A new multichannel filter, the vector Huber filter (VHF) is proposed which, by relying on multivariate estimation theory permits to simultaneously remove impulsive and Gaussian noise from color images, while preserving edges and other fine image details. The new filter is obtained by extending the classical gray-scale Huber filter to the multichannel case. By relying on robust estimation theory, the rationale behind the development of the new filter is discussed. An approximated version of the vector Huber filter (the A-VHF filter), is also introduced to reduce the computational burden and making filtering practical. The validity of the A-VHF filter is confirmed by the preliminary experimental results shown in the paper.

We propose near-lossless digital watermarking for copyright protection of remote sensing images. In particular, we show that, by forcing a maximum absolute difference between the original and watermarked scene, the near-lossless paradigm makes it possible to decrease the effect of watermarking on remote sensing applications to be carried out on the images. As an example, the effect of near-lossless watermarking on image classification is analyzed.

Calibration of the output device used for the reproduction of digital colour images (a color CRT in most cases) can either be achieved through conventional techniques involving mathematical modeling of the CRT, or through a novel neural-network-based scheme, introduced in this work. A Java-based system for CRT remote calibration is also presented, which allows the user to get rid of the computational burden necessary to train the neural network, or to estimate the parameters of the CRT model by relying on a set of measurements of the colours displayed by the CRT. Measurements can be avoided as well, by storing calibration data relative to a wide variety of CRTs and by using them to calibrate monitors with similar characteristics.

The large diffusion of multimedia products distributed through CD-ROMs (off-line) and the Internet (on-line) is raising many concerns regarding the preservation of authors' rights. On the other hand, these new publication methods appear to be very attractive for increasing business opportunities. The problem of electronic management of copyright has thus become very important and many projects are being carried out worldwide to deal with it. The aim of this paper is to survey the main concepts which electronic copyright management systems should be based on. In particular the requirements, the players and the key technologies are presented.

The architecture of an intelligent perception system (IPS) is analyzed, and the main problems related to its practical implementation are discussed. Particular attention has been devoted to the data fusion function, which initiates the process and gives information on the actual situation with the associated uncertainties; the hypotheses function, which takes into consideration the uncertainties in the correlated data and creates the best explanations of the fused data; the option function, which creates various response alternatives for each hypothesis simulating the resulting effects; and the response function, which realizes the planned actions so producing new stimuli and initializing other processing cycles. The architecture of the IPS is presented. >