Search

In the past few decades, several methods have been developed for despeckling synthetic aperture radar (SAR) images. A considerable number of them have been derived under the assumption of a fully-developed speckle model in which the multiplicative speckle noise is supposed to be a white process. Unfortunately, the transfer function of SAR acquisition systems can introduce a statistical correlation, which decreases the despeckling efficiency of such filters. In this paper, a whitening method is proposed for processing a complex image acquired by a SAR system. We demonstrate that the proposed approach allows the successful application of classical despeckling algorithms. First, we perform an estimation of the SAR system frequency response based on some statistical properties of the acquired image and by using realistic assumptions. Then, a decorrelation process is applied on the acquired image, taking into account the presence of point targets. Finally, the image is despeckled. The experimental results show that the despeckling filters achieve better performance when they are preceded by the proposed whitening method; furthermore, the radiometric characteristics of the image are preserved. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, two algorithms for multiplicative noise reduction, using the undecimated separable wavelet transform, are extended to the nonsubsampled contourlet (NSCT) domain. Such algorithms use either a maximum a posteriori (MAP) or a linear minimum mean square error (LMMSE) filtering approach, and involve the estimation of the moments of the NSCT coefficients up to the fourth order. The MAP filter relies on the conjecture that the NSCT coefficients follow a generalized Gaussian distribution (GGD), whose parameters locally vary. The extension of the denoising algorithms to the NSCT domain is not trivial, because several issues, related to the nonseparable implementation of the NSCT and the estimation of the moments, are to be considered to obtain viable solutions. Simulation results show that the MAP filter always outperforms the LMMSE one, confirming that the nonstationary GGD model is suitable for describing NSCT coefficients. Both denoising algorithms benefit from the multidirectional domain. However, the improvements on the LMMSE filter are greater than those on the MAP filter, showing that denoising in the NSCT domain is less effective when the nonstationary MAP estimator is used. [Copyright &y& Elsevier]

In this paper, we compare the performance of two different communication techniques for impulse radio ultra-wide-band (UWB) systems, which resort to impulsive modulations. These techniques can be applied in a short-range scenario where a central node synchronously communicates with several peripheral nodes. The first one is based on the pulse repetition according to the spreading factor value, whereas the second one relies on the cyclic prefix insertion and the detection in the frequency domain (FD). Since both techniques cause a throughput loss, they have to be compared both in terms of the performance and the maximum data rate that is afforded. An indoor scenario is considered, in which either low- or high-data-rate flows are synchronously transmitted by a central node in the presence of variable system loads. Lastly, alternative detection strategies are also taken into account, which are based on the partial knowledge of the channel parameters. The complexity analysis and simulation results show that the FD approach is effective for high data-rate transmission and in the presence of many data flows, whereas RAKE is more suitable in low-data-rate systems transmitting few data flows. [ABSTRACT FROM AUTHOR]

In this paper, a novel despeckling algorithm based on undecimated wavelet decomposition and maximum a posteriori estimation is proposed. Such a method represents an improvement with respect to the filter presented by the authors, and it is based on the same conjecture that the probability density functions (pdfs) of the wavelet coefficients follow a generalized Gaussian (GG) distribution. However, the approach introduced here presents two major novelties: 1) theoretically exact expressions for the estimation of the GG parameters are derived: such expressions do not require further assumptions other than the multiplicative model with uncorrelated speckle, and hold also in the case of a strongly correlated reflectivity; 2) a model for the classification of the wavelet coefficients according to their texture energy is introduced. This model allows us to classify the wavelet coefficients into classes having different degrees of heterogeneity, so that ad hoc estimation approaches can be devised for the different sets of coefficients. Three different implementations, characterized by different approaches for incorporating into the filtering procedure the information deriving from the segmentation of the wavelet coefficients, are proposed. Experimental results, carried out on both artificially speckled images and true synthetic aperture radar images, demonstrate that the proposed filtering approach outperforms the previous filters, irrespective of the features of the underlying reflectivity. [ABSTRACT FROM AUTHOR]

In this paper, we propose an original detection scheme for high rate short-range impulse radio ultra-wideband systems. The proposed receiver relies on both the introduction of the cyclic prefix at the transmitter and the use of a frequency domain multiuser detector at the receiver. Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) detection strategies have been investigated and compared with the classical RAKE, considering a scenario where several mobile terminals communicate with a base station in an indoor environment characterized by severe multipath propagation. The results show that the MMSE receiver achieves the best performance, irrespective of the number of active terminals, both in the uplink and in the downlink communications. Hence, the proposed approach is well suited in indoor wireless environments where the multipath propagation tends to increase the effects of both the inter-path and the inter-user interference. [ABSTRACT FROM AUTHOR]

In this paper, the performance of filter bank transceivers in the presence of a dispersive time-variant channel is investigated. It is well known that filter bank transceivers can be adapted to the channel transfer function to yield intersymbol interference (ISI) cancellation. When the channel is time variant, several problems arise, since the transceiver should be changed whenever the channel evolves. In this paper, we will allow both the transmitter and the receiver to change and satisfy the interference-free condition, under the assumption of a zero-padded block transmission. In this case, the optimum transmitter-receiver pair can be computed by using a singular value decomposition (SVD) of the channel matrix. A fast receiver adaptation based on SVD tracking is presented. Simulation results show that minimum performance loss with respect to the optimum receiver can be achieved for our reduced complexity receiver. [ABSTRACT FROM AUTHOR]

In this paper, a new despeckling method based on undecimated wavelet decomposition and maximum a posteriori (MAP) estimation is proposed. Such a method relies on the assumption that the probability density function (pdf) of each wavelet coefficient is generalized Gaussian (GG). The major novelty of the proposed approach is that the parameters of the GG pdf are taken to be space-varying within each wavelet frame. Thus, they may be adjusted to spatial image context, not only to scale and orientation. Since the MAP equation to be solved is a function of the parameters of the assumed pdf model, the variance and shape factor of the GG function are derived from the theoretical moments, which depend on the moments and joint moments of the observed noisy signal and on the statistics of speckle. The solution of the MAP equation yields the MAP estimate of the wavelet coefficients of the noise-free image. The restored SAR image is synthesized from such coefficients. Experimental results, carried out on both synthetic speckled images and true SAR images, demonstrate that MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain, without resorting to a logarithmic transformation. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of a generic filterbank transceiver in the presence of a carrier frequency offset. We propose a theoretical model to compute the error probability in the case of a generic frequency-selective channel. Moreover, the proposed method is also extended to deal with nonuniform, i.e., wavelet, transceivers. The accuracy of the model is evaluated by means of computer simulations, using several types of filterbank transceivers. Systems based on cyclic prefix (CP) and zero padding (ZP) are considered to avoid interblock interference (IBI) in frequency-selective channels. The analytical results obtained with the proposed method allow us to quickly compare different systems, characterized by a different filterbank selectivity, as well as by different methods to combat IBI (ZP or CP). [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of data-aided channel estimation in an MC-CDMA system with multiple transmitting antennas. First, we take into consideration a method proposed for OFDM with transmit diversity that relies on the frequency correlation of adjacent subchannels. Then, we propose a new method based on the assumption of a channel slowly varying with time. The performance of the two estimators has been evaluated in terms of mean square error (MSE) of channel estimates and bit error rate (BER), considering a different number of active users in the downlink case. We have considered two channels with different frequency selectivity. The results show that in the presence of a frequency selective channel the proposed method outperforms the method based on frequency correlation and it behaves more robustly against multi-user interference. [Copyright &y& Elsevier]

Every camera sensor leaves unique traces on the acquired images that can be thought of as a camera fingerprint. This work presents an efficient algorithm for clustering images based on their camera fingerprints. The algorithm performs a fast preliminary clustering based on a compressed representation of the camera fingerprints, then it refines the initial clusters using full-size fingerprints. The efficiency of the method is further improved by scanning the images according to a ranking index that depends on fingerprint estimation quality. The results confirm that the proposed method achieves a performance comparable to the state of the art approaches, with a significantly lower computational complexity, especially on large datasets. The method can also handle cases in which the number of clusters is much larger than the average size of the clusters. • The algorithm is composed of two stages of clustering: initial and fine clustering. • The initial clustering stage uses compressed fingerprints which significantly reduces computational cost and memory requirements. • The fine clustering stage uses average full fingerprints and enhances the quality of clusters. • The computational complexity of the clustering algorithm is much less than state-of-the-art algorithms on small, medium and large datasets. • The proposed algorithm is robust to N C ≫ S C problem i.e., when the number of clusters N C is much larger than size of cluster S C. [ABSTRACT FROM AUTHOR]

• Development of an efficient implementation of SparseHash. • Development of an approximated Fast SparseHash. • Theoretical analysis of SparseHash, in terms of preservation of Jaccard coefficient. • Theoretical analysis of SparseHash, in terms of Hamming distance in LSH • Numerical experiments on real datasets (text documents and metagenome clustering). Embeddings provide compact representations of signals in order to perform efficient inference in a wide variety of tasks. In particular, random projections are common tools to construct Euclidean distance-preserving embeddings, while hashing techniques are extensively used to embed set-similarity metrics, such as the Jaccard coefficient. In this letter, we theoretically prove that a class of random projections based on sparse matrices, called SparseHash, can preserve the Jaccard coefficient between the supports of sparse signals, which can be used to estimate set similarities. Moreover, besides the analysis, we provide an efficient implementation and we test the performance in several numerical experiments, both on synthetic and real datasets. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging is a trending technique in remote sensing that finds its application in many different areas, such as agriculture, mapping, target detection, food quality monitoring, etc. This technique gives the ability to remotely identify the composition of each pixel of the image. Therefore, it is a natural candidate for the purpose of landmine detection, thanks to its inherent safety and fast response time. In this paper, we will present the results of several studies that employed hyperspectral imaging for the purpose of landmine detection, discussing the different signal processing techniques used in this framework for hyperspectral image processing and target detection. Our purpose is to highlight the progresses attained in the detection of landmines using hyperspectral imaging and to identify possible perspectives for future work, in order to achieve a better detection in real-time operation mode. [ABSTRACT FROM AUTHOR]

Retrograde cardioplegia catheter displacement represents a troublesome complication, frequently forcing the surgeon to interrupt the operative procedure and cannulate newly the coronary sinus. However, this maneuver is time consuming, often implies the loss of surgical exposure, and exposes again the coronary sinus to the risk of iatrogenic injuries. We describe the use of an external security stitch through the muscular right atrial wall to avoid the displacement of a retrograde cardioplegia catheter and analyze the anatomic conditions which predispose to this complication. [ABSTRACT FROM AUTHOR]