Spatial compression of Seasat SAR imagery

The results of a study of the techniques for spatial compression of synthetic-aperture-radar (SAR) imagery are summarized. Emphasis is on image-data volume reduction for archive and online storage applications while preserving the image resolution and radiometric fidelity. A quantitative analysis of various techniques, including vector quantization (VQ) and adaptive discrete cosine transform (ADCT), is presented. Various factors such as compression ratio, algorithm complexity, and image quality are considered in determining the optimal algorithm. The compression system requirements are established for electronic access of an online archive system based on the results of a survey of the science community. The various algorithms are presented and their results evaluated considering the effects of speckle noise and the wide dynamic range inherent in SAR imagery     

Complex SAR imagery and speckle filtering for wave imaging

A method is described to predict the wavenumber dependence of the speckle component in spectra of synthetic aperture radar intensity images. Filtering of this component is an important step in recovering waveheight spectra for synthetic-aperture radar (SAR) images of the ocean, and an effective means of doing so is required for the 'wave mode' of the European satellite ERS-1. The method uses the correlation function of the corresponding complex images and has been tested using a variety of airborne and spaceborne imagery obtained over both land and sea. Examples are shown of both successful and unsuccessful applications of the method.<>     

Multi-aspect target detection for SAR imagery using hidden Markovmodels

Radar scattering from an illuminated object is often highly dependent on the target-sensor orientation. In typical synthetic aperture radar (SAR) imagery, the information in the multi-aspect target signatures is diffused in the image-formation process. In an effort to exploit the aspect dependence of the target signature, the authors employ a sequence of directional filters to the SAR imagery, thereby generating a sequence of subaperture images that recover the directional dependence of the target scattering. The scattering statistics are then used to design a hidden Markov model (HMM), wherein the orientation-dependent scattering statistics are exploited explicitly. This approach fuses information embodied in the orientation-dependent target signature under the assumption that. Both the target identity and orientation are unknown. Performance is assessed by considering the detection of tactical targets concealed in foliage, using measured foliage-penetrating (FOPEN) SAR data     

Non-Gaussian signal statistics in ocean SAR imagery

The authors have studied the significance of non-Gaussian signal statistics in some synthetic aperture radar (SAR) images of the ocean surface. The study consisted of calculating the amplitude histogram of the returned echoes from the images and comparing these with the Rayleigh- and Kν-distributions, corresponding to the Gaussian and non-Gaussian statistics, respectively. The images used were some C-band SAR data from the Canadian airborne SAR collected during the NORCSEX'88 campaign and some ERS-1 data collected during the NORCSEX'91 campaign. The analysis of the NORCSEX'88 data included studies of the dependency of the signal statistics on incidence angle and meteorological and imaging conditions. It was found, specifically at small incidence angles, that there was a significant deviation from Gaussian statistics. It was also found that when the wind was blowing against the waves, the deviation from Gaussian statistics was more pronounced than when the wind was blowing in the same direction as the waves were propagating. The study also showed a correlation between the signal statistics and the width of the SAR image spectra. At low incidence angles, this agrees with the interpretation that non-Gaussian statistics may be related to strong widebanded scattering events. However, since non-Gaussian statistics also were observed at incidence angles as high as 50°, it is evident that the modulation of the scattering cross section by the long waves is also an important factor. In addition, the analysis of the ERS-1 data showed that to account for the width of the SAR image spectra, an azimuth smearing term, due to short scene coherence time, had to be included. This was in the present work done by modeling the short-coherence-time-smearing as a Gaussian low-pass filter. By this procedure, the authors were able to obtain realistic estimates for the average scene coherence time of the SAR scenes     

Statistical analysis of multi-look polarimetric SAR imagery

With a multiplicative speckle model, this paper shows the multi-look polarimetric synthetic aperture radar (SAR) data obeys a generalized K-distribution. To validate this distribution model, the multi-look intensity K-distribution is particularly tested. The relationship between the heterogeneity coefficient of the scene and the proper statistical model is experimentally established. In addition, based on the results of the statistical analysis, an adaptive classification scheme is presented, and the improved classification shows the importance of the statistical analysis.     

基于极化似然比的极化SAR影像变化检测

由于数据获取困难等问题,目前SAR影像变化检测方法多基于幅度,而较少引入极化信息.针对此方面的不足,以极化SAR数据为研究对象,在分析多极化SAR影像极化特征及其分布模型的基础上,构建极化似然比检验模型,以此进行不同时相的多极化SAR数据地表地物变化程度分析,通过设定恒虚警率确定变化区域,最后考虑地物空间信息剔出斑点噪声引起的孤立检测结果.利用多极化SAR数据进行算法的验证,并与图像比值法进行比较,实验表明:基于极化似然比方法可以有效区分地物的变化情况,且变化检测精度要优于图像比值法.     

A simulation for spaceborne SAR imagery of a distributed, movingscene

A computer simulation that is designed to represent aspects of spaceborn synthetic-aperture radar (SAR) imagery of the ocean surface is presented. The simulation is unique in that a scatterer density (per resolution cell) is explicitly included, thus allowing the incorporation of various scattering natures, from purely specular to purely diffuse. The simulation may be applied to ocean surface wave imaging, since velocity bunching and scene coherence times are also included. Certain assumptions inherent in the velocity bunching formulation limit the applicability of the simulation in its present form to spaceborn SAR systems only. Two experiments based on this simulation are considered: (1) the effect of varying the target density; and (2) the effect of the mean scene coherence time in the imaging of a ocean swell system     

Information-theoretic bounds for authentication schemes

Consider the situation whereby each member of a sequence of n distinct messages from a finite source space is provided with an authentication check, generated using one and the same encoding rule selected from a finite space of such rules. Let P(n) be the expected probability that a spoofer, who observes such a sequence of messages and their corresponding authentication checks, but does not know the encoding rule in advance, succeeds in generating the correct authentication check for a different message in the source space. The purpose of this paper is to derive a lower bound for the average P _Nof the probabilities P(0), P(1),...;, P(N) in terms of the entropy of the space of encoding rules, and to derive necessary and sufficient conditions which the encoding scheme must satisfy in order to ensure that this bound cannot be exceeded.     

Analysis and processing of ultra wide-band SAR imagery for buriedlandmine detection

Experimental and theoretical results are presented for ultra wide-band (UWB) synthetic aperture radar (SAR) signatures of buried anti-tank and anti-personnel mines. Such are characterized by resonance-like peaks as well as valleys, across the 50-1200 MHz bandwidth considered. Consequently, frequency subbanding is used to highlight one target over another, of application to discriminating targets (mines) from clutter     

A note on SAR imagery of the ocean

An example of SAR imagery of the ocean surface including the Gulf Stream Boundary reported by Moskowitz [1] is used to discuss potential mechanisms of SAR image formation of the ocean. It is pointed out that images in addition to those due to modulation of surface scatterer strength may result from organized scatterer motions such as those due to currents or wave orbital velocities. The modulation of scattering cross section by large waves is expected to depend on the magnitude and direction of the wind, making the relationship between image strengths and wave amplitudes rather complicated. It is suggested that the effect of wave orbital accelerations upon azimuthal focus might provide a more direct measure of wave amplitude.     

Speckle reduction in multipolarization, multifrequency SAR imagery

An algorithm to take advantage of this polarization diversity to suppress the speckle effect with much less resolution broadening than using spatial filtering is discussed. The coupling between polarization channels is minimized by using local intensity ratios. The degree of speckle reduction is similar to two-look or three-look processing. The same algorithm can also be used to process multifrequency polarimetric SAR. For three-frequency aircraft SAR data speckle reduction equivalent to six-look processing can be achieved. Further speckle reduction is possible by applying speckle filters in the spatial domain. In addition, a vector speckle filter which operates simultaneously in the polarization and spatial domains is tested. Experimental results with simulated polarimetric SAR as well as one-look and multilook parametric SAR data demonstrate the effectiveness of these speckle reductions, with minimum resolution broadening and coupling between polarimetric and frequency channels. Comparisons with other algorithms are also made     

Two-dimensional adaptive block Kalman filtering of SAR imagery

A method for removing speckle from synthetic aperture radar (SAR) imagery by using 2-D adaptive block Kalman filtering is introduced. The image process is represented by an autoregressive model with a nonsymmetric half-plane (NSHP) region of support. New 2-D Kalman filtering equations are derived which taken into account not only the effect of speckles as multiplicative noise but also the effects of the additive receiver thermal noise and the blur. This method assumes local stationarity within a processing window, whereas the image can be assumed to be globally nonstationary. A recursive identification process using the stochastic Newton approach is also proposed which can be used on-line to estimate the filter parameters based upon the information within each new block of the image. Simulation results on several images are provided to indicate the effectiveness of the proposed method when used to remove the effects of speckle noise as well as those of the additive noise     

Multiscale segmentation and anomaly enhancement of SAR imagery

We present efficient multiscale approaches to the segmentation of natural clutter, specifically grass and forest, and to the enhancement of anomalies in synthetic aperture radar (SAR) imagery. The methods we propose exploit the coherent nature of SAR sensors. In particular, they take advantage of the characteristic statistical differences in imagery of different terrain types, as a function of scale, due to radar speckle. We employ a class of multiscale stochastic processes that provide a powerful framework for describing random processes and fields that evolve in scale. We build models representative of each category of terrain of interest (i.e., grass and forest) and employ them in directing decisions on pixel classification, segmentation, and anomalous behaviour. The scale-autoregressive nature of our models allows extremely efficient calculation of likelihoods for different terrain classifications over windows of SAR imagery. We subsequently use these likelihoods as the basis for both image pixel classification and grass-forest boundary estimation. In addition, anomaly enhancement is possible with minimal additional computation. Specifically, the residuals produced by our models in predicting SAR imagery from coarser scale images are theoretically uncorrelated. As a result, potentially anomalous pixels and regions are enhanced and pinpointed by noting regions whose residuals display a high level of correlation throughout scale. We evaluate the performance of our techniques through testing on 0.3-m resolution SAR data gathered with Lincoln Laboratory's millimeter-wave SAR.     

Change detection for thematic mapping by means of airbornemultitemporal polarimetric SAR imagery

The paper addresses the detection of changes in multitemporal polarimetric radar images, focusing on small objects and narrow linear features. The images were acquired at C- and L-band by the airborne EMISAR system. It is found that the radar intensities are better suited for change detection than the correlation coefficient and the phase difference between the co-polarized channels. In the case of linear features, there is no obvious difference between the C- and L-bands , and slight variations of the flight tracks are acceptable at look angles larger than 35 degrees. Theoretical detection thresholds are evaluated from the statistical distribution of the intensity ratio due to speckle. For the linear features and for urban environments, the observed thresholds are larger than the theoretical predictions. This is interpreted as an effect of radar intensity variations on length scales smaller than the spatial image resolution. The signature of urban areas is very sensitive to deviations between the flight tracks, and the sensitivity is larger at C-band than at L-band. On the other hand, the intensity contrast between buildings and the urban background is smaller at L-band and larger at C-band. For change detection, thresholds may have to be chosen separately for each object class because the intensity ratios of different object classes vary differently as a function of time     

Hierarchical stochastic modeling of SAR imagery forsegmentation/compression

There has been a growing interest in synthetic aperture radar (SAR) imaging on account of its importance in a variety of applications. One attribute leading to its gain in popularity is its ability to image terrain at extraordinary rates. Acquiring data at such rates, however, has drawbacks in the form of exorbitant costs in data storage and transmission over relatively slow channels; thus, addressing these problems is clearly important. To abate these and related costs, we propose a segmentation-driven compression technique using hierarchical stochastic modeling within a multiscale framework. Our approach to SAR image compression is unique in that we exploit the multiscale stochastic structure inherent in SAR imagery. This structure is well captured by a set of scale auto-regressive (AR) models that accurately characterize the evolution in scale of homogeneous regions of different classes of terrain. We thus use them to generate a multiresolution segmentation of the image. The segmentation is subsequently used in tandem with the corresponding models in a pyramid encoder to provide a robust, hierarchical compression technique that, in addition to coding the segmentation, achieves high compression ratios with impressive image quality     

几何模型约束的SAR图像建筑物提取

利用高分辨率SAR图像进行建筑物提取的常规方法是首先利用二次散射特征线确定建筑物边界, 然后利用叠掩、阴影等散射特征来提取建筑物高度.当建筑物目标走向与星载SAR方位向夹角较大时, 其二次散射特征不明显, 常规重建方法不能取得理想结果.针对这类建筑物目标, 在分析SAR图像上的散射特征为平行四边形条带的基础上, 提出一种基于几何模型约束的建筑物自动提取与三维重建方法.将该方法应用于TerraSAR-X聚束模式图像, 并对提取结果进行了分析和评价, 表明该方法能够有效提取建筑物目标及其三维信息.     

Information-theoretic distortion measures for speech recognition

A wide variety of speech recognition distortion measures have been proposed and tested, including some especially effective ones. It is shown that there is a general framework, based on the concepts of information theory, linking most of these measures. The distortion measure between any two speech spectra can be defined in terms of the distortions between the associated probability distributions. This general framework defines three broad families of distortion measures for speech recognition and provides a consistent way of combining the energy and the spectral information of a phonetic event. In addition, the cepstral-domain representation for several distortion measures is derived, allowing comparison of these measures in a domain that also yields convenient equations for their practical implementation     

移动通信终端SAR值测试方法研究

本文结合行业发展的现状,对移动通信终端的SAR值的技术标准和测试方法进行了研究,并提出了健康使用手机的若干建议,以培养公众健康使用手机的习惯。     

Information-theoretic inequalities for contoured probability distributions

We show that for a special class of probability distributions that we call contoured distributions, information-theoretic invariants and inequalities are equivalent to geometric invariants and inequalities of bodies in Euclidean space associated with the distributions. Using this, we obtain characterizations of contoured distributions with extremal Shannon and Renyi entropy. We also obtain a new reverse information-theoretic inequality for contoured distributions.     

The principle of speckle filtering in polarimetric SAR imagery

The principle of speckle reduction in polarimetry is reconsidered. It is shown that polarimetric data can be speckle reduced if and only if all the elements of the Mueller matrix are filtered, which is equivalent to filtering the scattering vector covariance matrix. Assuming that speckle is multiplicative and stationary, the algorithms proposed by S.L.Lee et al. (1991) and S.Goze et al. (1993) are extended to filter the covariance matrix of reciprocal and nonreciprocal targets on one-look and multilook images. The problem of estimation of the first- and second-order statistics of the four-channel speckle vector is discussed, and a solution is proposed for one-look and multilook images