一种基于提升小波的SAR图像有损压缩算法

该文根据合成孔径雷达(SAR)图像局部相关性较弱,存在相干斑噪声的特点,提出了一种基于提升小波的SAR图像有损压缩算法。它可有效去除相干斑噪声,提高计算精度和速度,改进SAR图像的压缩性能。该算法采用了嵌入式零树小波的编码方法,很好地利用小波系数的特性,使得输出的码流具有嵌入特性。利用大量的实际SAR图像对所提算法进行了仿真验证,并与其它图像压缩算法进行了对比分析,表明所提算法是有效的。     

Adaptive enhancement of compressed SAR images

Synthetic aperture radar (SAR) imagery is an important global all-weather surveillance and mapping satellite imagery system. As space-borne systems have a limited storage capacity, it is imperative to heavily compress SAR images, possible with lossy compression schemes. As a result, SAR images need to be enhanced in earth stations. The work reported in this paper aims to address the issue of compression artefact removal of SAR images in an adaptive manner. The SAR images, compressed using the JPEG utility at significantly low bit rates, are enhanced by adaptively removing coding artefacts and speckle noise. As edges carry significant information in satellite imagery, a significant edge image is used for edge enhancement with selective removal of noisy edges. Further, an image sharpness metric is proposed in this work to serve as an objective no-reference metric for measuring the sharpness of SAR images.     

MIMO雷达三维干涉诊断成像方法

2维合成孔径雷达(Synthetic Aperture Radar, SAR)和逆合成孔径雷达(Inverse Synthetic Aperture Radar, ISAR)成像是目标散射机理高分辨率分析和散射诊断测量的重要手段,现有被广泛采用的技术主要包括转台ISAR和导轨SAR成像技术。相比于传统的2维成像,3维成像可以提供目标局部散射中心在空间的3维位置和散射强度信息。因此,探索新的、可工程化实现与应用的目标3维成像技术是一项极具吸引力的工作。该文提出一种基于多输入多输出(Multiple-Input Multiple-Output, MIMO)阵列技术的3维干涉成像方法。首先,设计并试验了一种具有高孔径利用率和通过虚拟孔径实现干涉成像功能的MIMO阵列;其次,分析了MIMO阵列合成的两组虚拟孔径所成两幅2维雷达像的干涉相位与目标散射中心高度之间的关系,发展了MIMO雷达3维干涉成像算法;最后,通过数值仿真和原理样机实验验证了所提方法在目标散射机理分析和诊断测量应用中的可行性和有效性。      

利用对比度最大化实现SAP图像自聚焦

以对比度作为衡量图像聚焦程度的标准，研究了一种新颖的SAR图像自聚焦算法。该方法从图像域出发，通过在距离压缩相位历史域引入相位误差模型，从而改变聚上至图像对比度最大，完成相位误差的校正。对比度最大化算法的突出优点是无须在图像域分离出强点目标，因而特别适用于无任何明显特征的图像。仿真及实测数据处理结果证明了该方法的可行性。     

A wavelet transform coder supporting browsing and transmission of sea ice SAR imagery

A wavelet-transform-based algorithm for sea ice synthetic aperture radar (SAR) image data compression is presented. Compression of the relatively low resolution (100 m) SAR data is necessary to enable the transmission of such images from the Finnish Ice Service to users in the Baltic Sea. On board the ships, the SAR images are used for navigation purposes. Hence, in the visual appearance of the compressed image, special attention must be paid to the sharpness of small details. Several target-dependent features are incorporated in the compression scheme developed. The addition of these features was motivated by an examination of the wavelet coefficient statistics for the SAR data. In the quantization phase, the sensitivity characteristics of the human visual system were taken into account. As a result, the proposed algorithm deviates in several respects from the standard procedures used in wavelet-based compression. The algorithm requires the setting up of multiple user-defined parameters to satisfy the requirements of the users and data. This requires supervision of an expert, but also makes it flexible for many kinds of data and user requirements. The algorithm presented gives satisfactory results with a compression ratio of 20:1. Since only the location of ice-covered areas is of significance for ship traffic, the algorithm introduced contains an option to mask off open sea areas with the aid of an automatic open-water detection procedure. We also report the results of a user evaluation, in which the proposed algorithm is compared to the algorithm currently used by the Finnish Ice Service, as well as to the JPEG standard. The results of the evaluation favor the use of the proposed algorithm.     

The Recognition of Extended Targets: SAR Images for Level And Hilly Terrain

An experiment was performed using radar image simulation techniques to determine what a SAR image would look like for a collection of area extensive targets, first with flat underlying terrain and second, in the presence of moderate relief. Although compression, layover, and shadow are well known from the one-dimensional geometry analyses, it has not been previously demonstrated in a pictorial fashion what happens to the appearance of the same controlled reflectivity pattern, for level and hilly ground. It is not surprising to radargrammetrists that even modest elevation changes seriously affect the detection and recognition of boundaries and shapes. The image results clearly demonstrate these effects, and are valuable for many researchers who have previously used, or are just beginning to apply SAR imagery to crops and soils, minerals, and water resources assessment, etc. This research was performed during the course of an investigation to establish the performance of the Seasat-A SAR, in terms of user-oriented features, thus the radar system model and geometry are pertinent to that sensor, although the results can be applied to radar imaging in general. A review of range perspective imaging is included, since information extraction from radar imagery necessitates the knowledge of geometry/propagation effects.     

SAR复图像域上的噪声抑制和目标特征提取

基于SAR图像的稀疏先验,提出了一种基于l_k范数的复图像域正则化方法,用于SAR复图像的噪声抑制和目标特征提取.文中通过算法设计及其收敛性的研究,保证了该方法的可行性和稳健性.同时,基于正则化方法与广义岭估计的契合之处,提出了一种新的正则化参数的选取方法.理论分析和实验结果均表明,本文方法可操作性强,具有有效的噪声抑制和目标特征稀疏表示寻优功能.     

基于小波包变换的SAR原始数据压缩

该文介绍了小波包变换和网格编码量化的优点,结合合成孔径雷达(SAR)原始数据的特点,提出了基于小波包变换和网格编码量化的SAR原始数据压缩算法。利用模拟和实际数据分析了该压缩算法的性能,通过与其他原始数据压缩算法的比较说明了这一方法的有效性。     

基于曲面拟合的SAR图像分维特征提取方法

本文对 ＳＡＲ图像的目标统计特性进行了分析,并对原始 ＳＡＲ图像数据采用小波分解进行了乘性噪声抑制,提出了一种用最小二乘法拟合空间曲面的分维特征提取算法,并应用该方法对ＳＡＲ图像数据进行了实验,得到了理想的效果．     

采用格形算法对SAR图像进行压缩处理

文章提出了一种新的可用于合成孔径雷达的图像数据压缩技术。该技术基于格形编码的方案，人有比以往的压缩算法更为出色的特性，在星载和机载合成孔径雷达图像和原始数据的压缩上有着广泛的应用前景。文中给出了对机载雷达图像压缩后的实验结果和分析数据。     

Residual SAR focusing: an application to coherence improvement

The focusing quality of a SAR processor greatly depends on the accuracy of the system geometry estimate. Sometimes ancillary data do not provide enough accuracy, therefore autofocusing has to be performed to get the finest quality possible. A “residual” azimuth compression is introduced to show how a defocused image can be compensated by means of a monodimensional local operator. The residual transfer function that generates defocusing is then derived. The effects of the defocusing are shown on both a complex single SAR image and a SAR interferogram. SAR interferograms, however, are much more sensitive to defocusing than the single SAR image. Two algorithms have been developed to estimate, and compensate for, the defocusing in both the single SAR image and SAR interferometric cases. The processors select data suitable for estimating focusing parameters from the whole images by exploring Kurtosis (for single image focusing) or coherence (for interferometric autofocusing). The residual, short time-domain operator is then exploited to retrieve the focusing parameter values and, finally, to get the focused image. The limitations and accuracy of the algorithm in terms of parameter estimation are investigated. Experimental results, obtained from different SAR missions, are presented     

Capabilities of Dual-Frequency Millimeter Wave SAR With Monopulse Processing for Ground Moving Target Indication

Ground moving target indication (GMTI) for synthetic aperture radar (SAR) provides information on nonstatic objects in radar imagery of a static ground scene. An efficient approach for GMTI is the use of multichannel SAR systems for a space- and time-variant analysis of moving targets. This allows the indication, correction of position displacement, and estimation of radial velocity components of moving targets in a SAR image. All three steps are possible due to a determinable Doppler frequency shift in the radar signal caused by radial target movement. This paper focuses on the millimeter wave (mmW) SAR system MEMPHIS with multichannel amplitude-comparison monopulse data acquisition and the ability to use carrier frequencies of 35 and 94 GHz simultaneously, making it a dual-frequency SAR. This paper includes mmW-specific SAR GMTI considerations, an adaptive algorithm to collect velocity and position information on moving targets with mmW monopulse radar, and a discussion on GMTI blind speed elimination and target velocity ambiguity resolving by dual-frequency SAR. To determine the capabilities of both, system and algorithm, three large-scale experiments with MEMPHIS in different environments are presented     

一种基于勒让德拟合的SAR 后向投影自聚焦算法

对于合成孔径雷达(SAR)成像来说,后向投影(Back Projection, BP)算法是一种十分重要的时域成像方法。然而现有的自聚焦算法都是基于频域成像算法开发的,无法直接用于BP 聚焦图像的误差相位估计。针对这一问题,该文提出一种适用于BP 图像的自聚焦算法。该算法以图像锐度函数为目标函数,以待估计的相位校正值为自变量,通过坐标下降最优化算法循环迭代获得它们的最优估计。在问题求解中,该算法利用勒让德多项式来拟合目标函数,使得每次迭代的最优解可以解析地获得,避免了低效的线搜索过程。基于仿真数据和实测数据的实验验证了该算法的精确性和有效性。      

基于ω-k算法的宽测绘带星载SAR成像处理

本文提出了一种适用于宽测绘带星载SAR成像处理的改进ω-k算法.在用经典ω-k算法来处理星载SAR数据时,离参考距离越远图像形变和方位聚焦质量下降就越严重,这严重地限制了测绘带宽度.本文在ω-k算法的基础上提出了用等效视角补偿和等效速度补偿来校正图像形变和提高方位聚焦质量的改进算法.实验表明这种算法能够高效地对宽测绘带星载SAR数据进行精确成像处理.     

SAR speckle reduction using wavelet denoising and Markov random field modeling

The granular appearance of speckle noise in synthetic aperture radar (SAR) imagery makes it very difficult to visually and automatically interpret SAR data. Therefore, speckle reduction is a prerequisite for many SAR image processing tasks. In this paper, we develop a speckle reduction algorithm by fusing the wavelet Bayesian denoising technique with Markov-random-field-based image regularization. Wavelet coefficients are modeled independently and identically by a two-state Gaussian mixture model, while their spatial dependence is characterized by a Markov random field imposed on the hidden state of Gaussian mixtures. The Expectation-Maximization algorithm is used to estimate hyperparameters and specify the mixture model, and the iterated-conditional-modes method is implemented to optimize the state configuration. The noise-free wavelet coefficients are finally estimated by a shrinkage function based on local weighted averaging of the Bayesian estimator. Experimental results show that the proposed method outperforms standard wavelet denoising techniques in terms of the signal-to-noise ratio and the equivalent-number-of-looks measures in most cases. It also achieves better performance than the refined Lee filter.     

SAR图像舰船目标检测算法的对比研究

SAR图像舰船目标检测有二种经典算法:双参数CFAR算法和K-分布CFAR算法。本文分析了二种算法的特点,使用RADARSAT卫星不同模式SAR图像分别进行实验,给出二种算法的适应性。     

基于压缩感知的SAR图像压缩与重构方法

结合合成孔径雷达(SAR)图像特点,提出了一种基于压缩感知的SAR图像压缩与重构方法,并给出了具体的方法及详细流程.该方法首先将原始SAR图像进行分块处理,同时,利用离散小波变换(DWT)对分块结果进行稀疏处理,利用近似QR分解后的随机高斯矩阵对稀疏处理结果进行低维线性观测,实现了SAR图像的稀疏化表征与压缩.文中讨论的改进的正交匹配追踪(OMP)算法,与传统的OMP算法相比,改进的OMP算法在保证重构精度的前提下,可有效提高收敛速度.最后,通过离散小波反变换等处理获得最终的SAR图像重构结果.仿真实验结果证明所提方法的有效性与可行性.     

用ADSP21062高速信号处理系统实现机载SAR实时成像处理器的方位向处理

机载SAR实时成像处理器可以在载机飞行的同时获得高分辨率的SAR图像,对于实时监测、军事侦察等应用具有重要意义。实时成像处理器就是用高速数字信号处理系统来实时地实现SAR的成像算法。该文介绍SAR实时成像处理器方位向处理部分的研制,该部分采用了自行开发的、基于ADSP21062的高速信号处理系统,8片ADSP21062被安排在4个并行处理通道中,具有960MFLOPS的峰值处理速度,优化的软件设计保证了硬件资源的利用效率。仿真测试和外场实验证明了该系统的设计是成功的。该文对方位向处理部分的实现原理、硬件结构、软件设计进行了详细介绍。     

Landsat ETM+ and SAR image fusion based on generalized intensity Modulation

This work presents a novel multisensor image fusion algorithm, which extends panchrmomatic sharpening of multispectral (MS) data through intensity modulation to the integration of MS and synthetic aperture radar (SAR) imagery. The method relies on SAR texture, extracted by ratioing the despeckled SAR image to its low-pass approximation. SAR texture is used to modulate the generalized intensity (GI) of the MS image, which is given by a linear transform extending intensity-hue-saturation transform to an arbitrary number of bands. Before modulation, the GI is enhanced by injection of high-pass details extracted from the available panchrmomatic image by means of the "a/spl grave/-trous" wavelet decomposition. The texture-modulated panchrmomatic-sharpened GI replaces the GI calculated from the resampled original MS data. Then, the inverse transform is applied to obtain the fusion product. Experimental results are presented on Landsat-7 Enhanced Thematic Mapper Plus and European Remote Sensing 2 satellite images of an urban area. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, which can be usefully applied for both visual analysis and classification purposes.     

基于特征矢量匹配的SAR海洋图像舰船目标检测

根据SAR图像的基本特点 ,阐述了用DFBR场模型表达SAR图像的基本原理。在此基础上 ,通过提取SAR海洋图像中每个像素的分形值、分形模型拟合误差和方差统计量特征参数 ,结合图像像素的灰度值 ,形成一个对应于每个像素的特征矢量 ,并利用模糊数学的模糊子集概念 ,提出了一种基于特征矢量匹配的舰船目标检测方法。实际数据处理的结果表明 ,该方法具有较高的可靠性和准确性。