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Sample records for satellite sar imaging

  1. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

    Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...... on a seven-year ERS-1 and a four-year ERS-2 time series, the long term stability is found to be sufficient to allow a single calibration covering the entire mission period. A descending and an ascending orbit tandem pair of the ESA calibration site on Flevoland, suitable for calibration of ERS SAR processors...

  2. Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

    Directory of Open Access Journals (Sweden)

    Nina Merkle

    2017-06-01

    Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

  3. Origins and features of oil slicks in the Bohai Sea detected from satellite SAR images.

    Science.gov (United States)

    Ding, Yi; Cao, Conghua; Huang, Juan; Song, Yan; Liu, Guiyan; Wu, Lingjuan; Wan, Zhenwen

    2016-05-15

    Oil slicks were detected using satellite Synthetic Aperture Radar (SAR) images in 2011. We investigated potential origins and regional and seasonal features of oil slick in the Bohai Sea. Distance between oil slicks and potential origins (ships, seaports, and oil exploitation platforms) and the angle at which oil slicks move relative to potential driving forces were evaluated. Most oil slicks were detected along main ship routes rather than around seaports and oil exploitation platforms. Few oil slicks were detected within 20km of seaports. Directions of oil slicks movement were much more strongly correlated with directions of ship routes than with directions of winds and currents. These findings support the premise that oil slicks in the Bohai Sea most likely originate from illegal disposal of oil-polluted wastes from ships. Seasonal variation of oil slicks followed an annual cycle, with a peak in August and a trough in December.

  4. Satellite SAR geocoding with refined RPC model

    Science.gov (United States)

    Zhang, Lu; Balz, Timo; Liao, Mingsheng

    2012-04-01

    Recent studies have proved that the Rational Polynomial Camera (RPC) model is able to act as a reliable replacement of the rigorous Range-Doppler (RD) model for the geometric processing of satellite SAR datasets. But its capability in absolute geolocation of SAR images has not been evaluated quantitatively. Therefore, in this article the problems of error analysis and refinement of SAR RPC model are primarily investigated to improve the absolute accuracy of SAR geolocation. Range propagation delay and azimuth timing error are identified as two major error sources for SAR geolocation. An approach based on SAR image simulation and real-to-simulated image matching is developed to estimate and correct these two errors. Afterwards a refined RPC model can be built from the error-corrected RD model and then used in satellite SAR geocoding. Three experiments with different settings are designed and conducted to comprehensively evaluate the accuracies of SAR geolocation with both ordinary and refined RPC models. All the experimental results demonstrate that with RPC model refinement the absolute location accuracies of geocoded SAR images can be improved significantly, particularly in Easting direction. In another experiment the computation efficiencies of SAR geocoding with both RD and RPC models are compared quantitatively. The results show that by using the RPC model such efficiency can be remarkably improved by at least 16 times. In addition the problem of DEM data selection for SAR image simulation in RPC model refinement is studied by a comparative experiment. The results reveal that the best choice should be using the proper DEM datasets of spatial resolution comparable to that of the SAR images.

  5. A DHIP Algorithm for SAR Satellite Imaging Planning%SAR卫星成像任务规划的DHIP方法

    Institute of Scientific and Technical Information of China (English)

    朱小满; 王钧; 李军; 景宁

    2011-01-01

    The emergence of earth observing satellite with Synthetic Aperture Radar (SAR) onboard provides a significant instrument to obtain geo-space information. This paper studies rightly on the SAR satellite imaging planning problem. Firstly, the general imaging process of SAR satellite is described to illustrate that the methods pertinent to optical satellite imaging planning are no longer suitable for the problem of a SAR satellite imaging planning. Secondly, the main influential constraints of SAR satellite are induced. Based on that, an approach called DHIP (Double Hierarchy Insert Planning) is proposed and described detailedly. The main idea of this method is to form an optimized scheme by tentatively inserting every candidate imaging request through two hierarchies, which are the hierarchy of SAR opening and closing, and that of photographing, by a checking while constructing method. The final experimental results show that the DHIP algorithm works fast and is able to get a satisfying scheme under general circumstances.%合成孔径雷达(SAR)卫星的出现为获取地球空间信息提供了重要手段,本文研究的即是SAR卫星成像任务规划问题.首先描述了SAR成像卫星的一般工作流程,说明针对可见光卫星进行成像任务规划的方法不再适用于SAR成像卫星任务规划;然后归纳了影响SAR卫星成像的主要约束.在此基础上,提出了双层插入规划(DHIP)方法,该方法将待规划任务在星载SAR开关机信息元组级和成像信息元组级两个层级上逐次进行试探性插入,采用边构造边检测的方法获得该问题的优化解.实验结果表明,该方法计算速度快,可以有效解决SAR卫星成像任务规划问题.

  6. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    KAUST Repository

    Wang, Teng

    2015-09-05

    Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

  7. Exploitation of amplitude and phase of satellite SAR images for landslide mapping: the case of Montescaglioso (South Italy)

    Science.gov (United States)

    Raspini, Federico; Ciampalini, Andrea; Lombardi, Luca; Nocentini, Massimiliano; Gigli, Giovanni; Casagli, Nicola; Del Conte, Sara; Ferretti, Alessandro

    2016-04-01

    Pre- event and event landslide deformations have been detected and measured for the landslide that occurred on 3 December 2013 on the south-western slope of the Montescaglioso village (Basilicata Region, southern Italy). The event, triggered by prolonged rainfalls, created significant damage to buildings and local infrastructures. Ground displacements have been mapped through an integrated analysis based on a series of high resolution SAR (Synthetic Aperture Radar) images acquired by the Italian constellation of satellites COSMO-SkyMed. Analysis has been performed by exploiting both phase (through multi-image SAR interferometry) and amplitude information (through speckle tracking techniques) of the satellite images. SAR Interferometry, applied to images taken before the event, revealed a general pre-event movement, in the order of a few mm/yr, in the south-western slope of the Montescaglioso village. Highest pre-event velocities, ranging between 8 and 12 mm/yr, have been recorded in the sector of the slope where the first movement of the landslide took place. Speckle tracking, applied to images acquired before and after the event, allowed the retrieval of the 3D deformation field produced by the landslide. It also showed that ground displacements produced by the landslide have a dominant SSW component, with values exceeding 10 m for large sectors of the landslide area, with local peaks of 20 m in its central and deposit areas. Two minor landslides with a dominant SSE direction, which were detected in the upper parts of the slope, likely also occurred as secondary phenomena as consequence of the SSW movement of the main Montescaglioso landslide. This work demonstrates that this complementary approach, based on the synergistic exploitation of phase and amplitude SAR data, can become a powerful tool for landslide investigation, allowing the detection of slow, precursory deformation patterns as well the retrieval of full 3D surface displacement fields caused by large

  8. Satellite sar detection of hurricane helene (2006)

    DEFF Research Database (Denmark)

    Ju, Lian; Cheng, Yongcun; Xu, Qing

    2013-01-01

    In this paper, the wind structure of hurricane Helene (2006) over the Atlantic Ocean is investigated from a C-band RADARSAT-1 synthetic aperture radar (SAR) image acquired on 20 September 2006. First, the characteristics, e.g., the center, scale and area of the hurricane eye (HE) are determined....... There is a good agreement between the SAR-estimated HE center location and the best track data from the National Hurricane Center. The wind speeds at 10 m above the ocean surface are also retrieved from the SAR data using the geophysical model function (GMF), CMOD5, and compared with in situ wind speed...... observations from the stepped frequency microwave radiometer (SFMR) on NOAA P3 aircraft. All the results show the capability of hurricane monitoring by satellite SAR. Copyright © 2013 by the International Society of Offshore and Polar Engineers (ISOPE)....

  9. Multiangle Bistatic SAR Imaging and Fusion Based on BeiDou-2 Navigation Satellite System

    Directory of Open Access Journals (Sweden)

    Zeng Tao

    2015-01-01

    Full Text Available Bistatic Synthetic Aperture Radar (BSAR based on the Global Navigation Service System (GNSSBSAR uses navigation satellites as radar transmitters, which are low in cost. However, GNSS-BSAR images have poor resolution and low Signal-to-Noise Ratios (SNR. In this paper, a multiangle observation and data processing strategy are presented based on BeiDou-2 navigation satellite imagery, from which twenty-six BSAR images in different configurations are obtained. A region-based fusion algorithm using region of interest segmentation is proposed, and a high-quality fusion image is obtained. The results reveal that the multiangle imaging method can extend the applications of GNSS-BSAR.

  10. Design and Implementation of a Real-time Processing System of Full Resolution Quick-look Image of HJ-1 Environmental Satellite C SAR Based on High Performance Cluster

    Directory of Open Access Journals (Sweden)

    Li Jing-shan

    2014-06-01

    Full Text Available This study is concerned with the design and implementation of a real-time processing system of full resolution quick-look image of HJ-1 environmental satellite C SAR based on high-performance clusters. The system processes the first quick-look SAR image on December 9, 2012. The results show that the design and implementation of the quick-look processing system satisfies the real-time SAR image processing performance requirements at full resolution. Moreover, this system is the first real-time business system of full-resolution quick-look spaceborne SAR images in China.

  11. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  12. Combined Use of SAR and Optical Satellite Images for Landscape Diversity Assessment

    Science.gov (United States)

    Kuchma, Tetyana

    2016-08-01

    Land cover change analysis is essential for effective land use management and biodiversity conservation. The advantages of Sentinel-1 and Landsat-8 image fusion for land cover classification and landscape diversity maps development were studied. The methodology of landscape metrics interpretation for sustainable land use planning is developed and tested on agricultural landscapes in Ukraine.

  13. Bistatic SAR: Imagery & Image Products.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Wahl, Daniel E.; Jakowatz, Charles V,

    2014-10-01

    While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

  14. 利用小波变换抑制星载SAR图象的斑点噪声%Speckle Restraint of Satellite SAR Image Using Wavelet Transform

    Institute of Scientific and Technical Information of China (English)

    胡召玲; 郭达志; 盛业华

    2001-01-01

    A speckle restraint algorithm was described for satellite SAR image using wavelet transform. The SAR image was decomposed using appropriate wavelet bases, and the contribution of speckle to wavelet coefficients was analyzed. Based on the multiplicative relation between speckle and gray and the correlation of speckle, a suitable threshold was selected. The SAR image after speckle restraining was reconstructed using wavelet reconstruction technique. The experiment shows that speckle can be effectively restrained using this algorithm.%利用小波变换技术对星载合成孔径雷达(SAR)图象斑点噪声进行抑制与滤除.选择合适的小波基对SAR图象进行小波分解,分析噪声对小波系数的贡献;针对噪声与图象灰度之间的乘性关系和SAR图象斑点噪声在空间上相关的特点设置适当的阈值,在小波域内滤波;通过小波重构技术获得滤波后的SAR图象.实验证明,该方法能有效地抑制SAR图象中的斑点噪声.

  15. System Design and In-orbit Verification of the HJ-1-C SAR Satellite

    Directory of Open Access Journals (Sweden)

    Zhang Run-ning

    2014-06-01

    Full Text Available HJ-1-C is a SAR satellite owned by the Chinese Environment and Natural Disaster Monitoring constellation, and works together with the optical satellites HJ-1-A/B for monitoring environment and natural disasters. In this paper, the system design and characteristics of the first Chinese civil SAR satellite are described. In addition, the interface relation between SAR payload and platform is studied. Meanwhile, the data transmission capability, attitude, power, and temperature control that support SAR imaging are reviewed. Finally, the corresponding in-orbit verification results are presented.

  16. A Review of Spaceborne SAR Algorithm for Image Formation

    Directory of Open Access Journals (Sweden)

    Li Chun-sheng

    2013-03-01

    Full Text Available This paper firstly reviews the history and trends in development of spaceborne Synthetic Aperture Radar (SAR satellite technology in American and European countries. Besides, the basic information of the launched satellites and the future satellite plans are introduced. Then this paper summaries and assorts the imaging algorithm of spaceborn SAR satellite and analyzes the advantages and disadvantages of each algorithm. Moreover, the scope and the application status of each algorithm are presented. And then the paper elaborates trends of SAR imaging algorithm, which mainly introduces the algorithms based on compressive sensing theory and new image modes, and the results of simulation are also illustrated. At last, the paper summaries the development direction of spaceborne SAR imaging algorithm.

  17. Satellite sar detection of hurricane helene (2006)

    DEFF Research Database (Denmark)

    Ju, Lian; Cheng, Yongcun; Xu, Qing;

    2013-01-01

    In this paper, the wind structure of hurricane Helene (2006) over the Atlantic Ocean is investigated from a C-band RADARSAT-1 synthetic aperture radar (SAR) image acquired on 20 September 2006. First, the characteristics, e.g., the center, scale and area of the hurricane eye (HE) are determined...

  18. SAR Image Enhancement using Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — In this paper, we propose a novel approach to reduce the noise in Synthetic Aperture Radar (SAR) images using particle filters. Interpretation of SAR images is a...

  19. Convolutional Neural Networks for SAR Image Segmentation

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Nobel-Jørgensen, Morten

    2015-01-01

    Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

  20. Comparing satellite SAR and wind farm wake models

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Vincent, P.; Husson, R.

    2015-01-01

    The aim of the paper is to present offshore wind farm wake observed from satellite Synthetic Aperture Radar (SAR) wind fields from RADARSAT-1/-2 and Envisat and to compare these wakes qualitatively to wind farm wake model results. From some satellite SAR wind maps very long wakes are observed. Th...

  1. SAR Image Segmentation using Vector Quantization Technique on Entropy Images

    CERN Document Server

    Kekre, H B; Sarode, Tanuja K

    2010-01-01

    The development and application of various remote sensing platforms result in the production of huge amounts of satellite image data. Therefore, there is an increasing need for effective querying and browsing in these image databases. In order to take advantage and make good use of satellite images data, we must be able to extract meaningful information from the imagery. Hence we proposed a new algorithm for SAR image segmentation. In this paper we propose segmentation using vector quantization technique on entropy image. Initially, we obtain entropy image and in second step we use Kekre's Fast Codebook Generation (KFCG) algorithm for segmentation of the entropy image. Thereafter, a codebook of size 128 was generated for the Entropy image. These code vectors were further clustered in 8 clusters using same KFCG algorithm and converted into 8 images. These 8 images were displayed as a result. This approach does not lead to over segmentation or under segmentation. We compared these results with well known Gray L...

  2. Design and Analysis of HJ-1-C Satellite SAR Antenna

    Directory of Open Access Journals (Sweden)

    Zheng Shi-kun

    2014-06-01

    Full Text Available With truss deployable mesh parabolic reflector, the HJ-1-C SAR antenna has complex structure and multiple steps during the deployed processing. The design of the antenna is difficult in terms of deployed reliability and electrical performance. This paper makes intensive research on system, structure and electrical design, and the analysis of mechanical and thermal performance in the actual space conditions is also presented. The successful deploying in orbit and high image quality of the HJ-1-C satellite indicate that the mechanical, electronic, thermal and reliability design of the antenna satisfy the project requirement, and these research provides valuable experience for the design of the centralized mesh parabolic SAR antenna.

  3. An easy to use ArcMap based texture analysis program for extraction of flooded areas from TerraSAR-X satellite image

    Science.gov (United States)

    Pradhan, Biswajeet; Hagemann, Ulrike; Shafapour Tehrany, Mahyat; Prechtel, Nikolas

    2014-02-01

    Extraction of the flooded areas from synthetic aperture radar (SAR) and especially TerraSAR-X data is one of the most challenging tasks in the flood management and planning. SAR data due to its high spatial resolution and its capability of all weather conditions makes a proper choice for tropical countries. Texture is considered as an effective factor in distinguishing the classes especially in SAR imagery which records the backscatters that carry information of kind, direction, heterogeneity and relationship of the features. This paper put forward a computer program for texture analysis for high resolution radar data. Texture analysis program is introduced and discussed using the gray-level co-occurrence matrix (GLCM). To demonstrate the ability and correctness of this program, a test subset of TerraSAR-X imagery from Terengganu area, Malaysia was analyzed and pixel-based and object-based classification were attempted. The thematic maps derived by pixel-based method could not achieve acceptable visual interpretation and for that reason no accuracy assessment was performed on them. The overall accuracy achieved by object-based method was 83.63% with kappa coefficient of 0.8. Results on image texture classification showed that the proposed program is capable for texture analysis in TerraSAR-X image and the obtained textural analysis resulted in high classification accuracy. The proposed texture analysis program can be used in many applications such as land use/cover (LULC) mapping, hazard studies and many other applications.

  4. Copernicus Sentinel-1 Satellite And C-SAR Instrument

    Science.gov (United States)

    Panetti, Aniceto; Rostan, Friedhelm; L'Abbate, Michelangelo; Bruno, Claudio; Bauleo, Antonio; Catalano, Toni; Cotogni, Marco; Galvagni, Luigi; Pietropaolo, Andrea; Taini, Giacomo; Venditti, Paolo; Huchler, Markus; Torres, Ramon; Lokaas, Svein; Bibby, David

    2013-12-01

    The Copernicus Sentinel-1 Earth Radar Observatory, a mission funded by the European Union and developed by ESA, is a constellation of two C-band radar satellites. The satellites have been conceived to be a continuous and reliable source of C-band SAR imagery for operational applications such as mapping of global landmasses, coastal zones and monitoring of shipping routes. The Sentinel-1 satellites are built by an industrial consortium led by Thales Alenia Space Italia as Prime Contractor and with Astrium GmbH as SAR Instrument Contractor. The paper describes the general satellite architecture, the spacecraft subsystems, AIT flow and the satellite key performances. It provides also an overview on the C-SAR Instrument, its development status and pre- launch SAR performance prediction.

  5. SAR Image Complex Pixel Representations

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    Complex pixel values for Synthetic Aperture Radar (SAR) images of uniform distributed clutter can be represented as either real/imaginary (also known as I/Q) values, or as Magnitude/Phase values. Generally, these component values are integers with limited number of bits. For clutter energy well below full-scale, Magnitude/Phase offers lower quantization noise than I/Q representation. Further improvement can be had with companding of the Magnitude value.

  6. The Accuratre Signal Model and Imaging Processing in Geosynchronous SAR

    Science.gov (United States)

    Hu, Cheng

    With the development of synthetic aperture radar (SAR) application, the disadvantage of low earth orbit (LEO) SAR becomes more and more apparent. The increase of orbit altitude can shorten the revisit time and enlarge the coverage area in single look, and then satisfy the application requirement. The concept of geosynchronous earth orbit (GEO) SAR system is firstly presented and deeply discussed by K.Tomiyasi and other researchers. A GEO SAR, with its fine temporal resolution, would overcome the limitations of current imaging systems, allowing dense interpretation of transient phenomena as GPS time-series analysis with a spatial density several orders of magnitude finer. Until now, the related literatures about GEO SAR are mainly focused in the system parameter design and application requirement. As for the signal characteristic, resolution calculation and imaging algorithms, it is nearly blank in the related literatures of GEO SAR. In the LEO SAR, the signal model analysis adopts the `Stop-and-Go' assumption in general, and this assumption can satisfy the imaging requirement in present advanced SAR system, such as TerraSAR, Radarsat2 and so on. However because of long propagation distance and non-negligible earth rotation, the `Stop-and-Go' assumption does not exist and will cause large propagation distance error, and then affect the image formation. Furthermore the long propagation distance will result in the long synthetic aperture time such as hundreds of seconds, therefore the linear trajectory model in LEO SAR imaging will fail in GEO imaging, and the new imaging model needs to be proposed for the GEO SAR imaging processing. In this paper, considering the relative motion between satellite and earth during signal propagation time, the accurate analysis method for propagation slant range is firstly presented. Furthermore, the difference between accurate analysis method and `Stop-and-Go' assumption is analytically obtained. Meanwhile based on the derived

  7. Imaging Algorithm for Bistatic SAR Based on GNSS Signal

    Directory of Open Access Journals (Sweden)

    Tian Wei-ming

    2013-03-01

    Full Text Available In this paper imaging processing method for Bistatic Synthetic Aperture Radar (BiSAR utilizing navigation satellite is investigated. Considering the special problems of using Global Navigation Satellite System (GNSS signal to form SAR image, direct signal is used to estimate range migration parameters and range migration is corrected in azimuth time domain. Doppler sensitivity of phase-coded signal was solved by Doppler compensation. Through fitting the Doppler phase history with high-order polynomial, Doppler phase history is accurately approximated and azimuth compression is implemented by de-chirp processing. Through simulation and experimental data processing, the proposed method is verified.

  8. Spaceborne SAR Imaging Algorithm for Coherence Optimized.

    Directory of Open Access Journals (Sweden)

    Zhiwei Qiu

    Full Text Available This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR research and application.

  9. Precision Rectification of Airborne SAR Image

    DEFF Research Database (Denmark)

    Dall, Jørgen; Liao, M.; Zhang, Zhe

    1997-01-01

    A simple and direct procedure for the rectification of a certain class of airborne SAR data is presented. The relief displacements of SAR data are effectively removed by means of a digital elevation model and the image is transformed to the ground coordinate system. SAR data from the Danish EMISAR...... for the application of SAR data in the difficult process of map revision and updating....

  10. Building Damage Estimation by Integration of Seismic Intensity Information and Satellite L-band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Nobuoto Nojima

    2010-09-01

    Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.

  11. Refocusing vibrating targets in SAR images

    Science.gov (United States)

    Wang, Qi; Santhanam, Balu; Pepin, Matthew; Atwood, Tom; Hayat, Majeed M.

    2012-06-01

    In synthetic-aperture radar (SAR) returned signals, ground-target vibrations introduce a phase modulation that is linearly proportional to the vibration displacement. Such modulation, termed the micro-Doppler effect, introduces ghost targets along the azimuth direction in reconstructed SAR images that prevents SAR from forming focused images of the vibrating targets. Recently, a discrete fractional Fourier transform (DFrFT) based method was developed to estimate the vibration frequencies and instantaneous vibration accelerations of the vibrating targets from SAR returned signals. In this paper, a demodulation-based algorithm is proposed to reconstruct focused SAR images of vibrating targets by exploiting the estimation results of the DFrFT-based vibration estimation method. For a single-component harmonic vibration, the history of the vibration displacement is first estimated from the estimated vibration frequency and the instantaneous vibration accelerations. Then a reference signal whose phase is modulated by the estimated vibration displacement with a delay of 180 degree is constructed. After that, the SAR phase history from the vibration target is multiplied by the reference signal and the vibration-induced phase modulation is canceled. Finally, the SAR image containing the re-focused vibration target is obtained by applying the 2-D Fourier transform to the demodulated SAR phase history. This algorithm is applied to simulated SAR data and successfully reconstructs the SAR image containing the re-focused vibrating target.

  12. Two dimensional estimates from ocean SAR images

    Directory of Open Access Journals (Sweden)

    J. M. Le Caillec

    1996-01-01

    Full Text Available Synthetic Aperture Radar (SAR images of the ocean yield a lot of information on the sea-state surface providing that the mapping process between the surface and the image is clearly defined. However it is well known that SAR images exhibit non-gaussian statistics and that the motion of the scatterers on the surface, while the image is being formed, may yield to nonlinearities. The detection and quantification of these nonlinearities are made possible by using Higher Order Spectra (HOS methods and more specifically, bispectrum estimation. The development of the latter method allowed us to find phase relations between different parts of the image and to recognise their level of coupling, i.e. if and how waves of different wavelengths interacted nonlinearly. This information is quite important as the usual models assume strong nonlinearities when the waves are propagating in the azimuthal direction (i.e. along the satellite track and almost no nonlinearities when propagating in the range direction. In this paper, the mapping of the ocean surface to the SAR image is reinterpreted and a specific model (i.e. a Second Order Volterra Model is introduced. The nonlinearities are thus explained as either produced by a nonlinear system or due to waves propagating into selected directions (azimuth or range and interacting during image formation. It is shown that quadratic nonlinearities occur for waves propagating near the range direction while for those travelling in the azimuthal direction the nonlinearities, when present, are mostly due to wave interactions but are almost completely removed by the filtering effect coming from the surface motion itself (azimuth cut-off. An inherent quadratic interaction filtering (azimuth high pass filter is also present. But some other effects, apparently nonlinear, are not detected with the methods described here, meaning that either the usual relation developed for the Ocean-to-SAR transform is somewhat incomplete

  13. Noise Removal in SAR Images using Orthonormal Ridgelet Transform

    Directory of Open Access Journals (Sweden)

    A. Ravi,

    2015-05-01

    Full Text Available Development in the field of image processing for reducing speckle noise from digital images/satellite images is a challenging task for image processing applications. Previously many algorithms were proposed to de-speckle the noise in digital images. Here in this article we are presenting experimental results on de-speckling of Synthetic Aperture RADAR (SAR images. SAR images have wide applications in remote sensing and mapping the surfaces of all planets. SAR can also be implemented as "inverse SAR" by observing a moving target over a substantial time with a stationary antenna. Hence denoising of SAR images is an essential task for viewing the information. Here we introduce a transformation technique called ―Ridgelet‖, which is an extension level of wavelet. Ridgelet analysis can be done in the similar way how wavelet analysis was done in the Radon domain as it translates singularities along lines into point singularities under different frequencies. Simulation results were show cased for proving that proposed work is more reliable than compared to other despeckling processes, and the quality of de-speckled image is measured in terms of Peak Signal to Noise Ratio and Mean Square Error.

  14. Composite SAR imaging using sequential joint sparsity

    Science.gov (United States)

    Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.

    2017-06-01

    This paper investigates accurate and efficient ℓ1 regularization methods for generating synthetic aperture radar (SAR) images. Although ℓ1 regularization algorithms are already employed in SAR imaging, practical and efficient implementation in terms of real time imaging remain a challenge. Here we demonstrate that fast numerical operators can be used to robustly implement ℓ1 regularization methods that are as or more efficient than traditional approaches such as back projection, while providing superior image quality. In particular, we develop a sequential joint sparsity model for composite SAR imaging which naturally combines the joint sparsity methodology with composite SAR. Our technique, which can be implemented using standard, fractional, or higher order total variation regularization, is able to reduce the effects of speckle and other noisy artifacts with little additional computational cost. Finally we show that generalizing total variation regularization to non-integer and higher orders provides improved flexibility and robustness for SAR imaging.

  15. Geo-correction Algorithm Based on Equivalent RD Model for ScanSAR of HJ-1-C Satellite

    Directory of Open Access Journals (Sweden)

    Liu Jia-yin

    2014-06-01

    Full Text Available HJ-1-C satellite is the first Synthetic Aperture Radar (SAR satellite for civilian use in China, and it has a strip and scan mode. According to the characteristics of the ScanSAR of the HJ-1-C satellite, a geo-correction algorithm based on an equivalent RD model has been outlined in this paper on the basis of an ECS image processing algorithm and a traditional Range-Doppler location method. An azimuth mosaic was presented by a time series relationship, then the different burst was stitched by range, and the equivalent parameters were fitted to locations on the RD model. Finally, the ScanSAR image was geo-corrected. The HJ-1-C satellite data results showed that the location accuracy of ScanSAR for the HJ-1-C satellite was less than 100 m, and the geo-correction algorithm was realized in 10 s in fewer than 24 parallel cores.

  16. Frequency synchronization scheme for parasitical BiSAR with GNSS satellites as illuminator

    Science.gov (United States)

    Tian, Weiming; Zeng, Tao; Hu, Cheng

    Bistatic Synthetic Aperture Radar (BiSAR) has a lot of advantages comparing with monostatic counterpart. What is more, parasitical BiSAR can utilize the existing Global Navigation Satel-lite System (GNSS) satellites to compose parasitical BiSAR system and form remote-sensing image. As performance of frequency synchronization scheme is crucial to BiSAR system, fre-quency synchronization scheme must be well designed. In fact high-precision frequency syn-chronization is required to obtain navigation data and assist positioning in GNSS receiver. In GNSS receivers, transient carrier frequency is tracked by digital Phase-Locked Loop (PLL). PLL method is applied to estimate frequency synchronization error and this has been verified in the primary experiment. Through tracking the carrier transient frequency of direct signal, frequency synchronization error can be obtained from the transient frequency when theoretical Doppler is calculated from ephemeris data.

  17. Bistatic SAR: Signal Processing and Image Formation.

    Energy Technology Data Exchange (ETDEWEB)

    Wahl, Daniel E.; Yocky, David A.

    2014-10-01

    This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

  18. Concept of an Effective Sentinel-1 Satellite SAR Interferometry System

    OpenAIRE

    2016-01-01

    This brief study introduces a partially working concept being developed at IT4Innovations supercomputer (HPC) facility. This concept consists of several modules that form a whole body of an efficient system for observation of terrain or objects displacements using satellite SAR interferometry (InSAR). A metadata database helps to locate data stored in various storages and to perform basic analyzes. A special database has been designed to describe Sentinel-1 data, on its burst level. Custom Se...

  19. Controlling Data Collection to Support SAR Image Rotation

    Science.gov (United States)

    Doerry, Armin W.; Cordaro, J. Thomas; Burns, Bryan L.

    2008-10-14

    A desired rotation of a synthetic aperture radar (SAR) image can be facilitated by adjusting a SAR data collection operation based on the desired rotation. The SAR data collected by the adjusted SAR data collection operation can be efficiently exploited to form therefrom a SAR image having the desired rotational orientation.

  20. Satellite SAR data assessment for Silk Road archaeological prospection

    Science.gov (United States)

    Chen, Fulong; Lasaponara, Rosa; Masini, Nicola; Yang, Ruixia

    2015-04-01

    The development of Synthetic Aperture Radar (SAR) in terms of multi-band, multi-polarization and high-resolution data, favored the application of this technology also in archaeology [1]. Different approaches based on both single and multitemporal data analysis, exploiting the backscattering and the penetration of radar data, have been used for a number of archaeological sites and landscapes [2-5]. Nevertheless, the capability of this technology in archaeological applications has so far not been fully assessed. It lacks a contribution aimed at evaluating the potential of SAR technology for the same study area by using different bands, spatial resolutions and data processing solutions. In the framework of the Chinese-Italian bilateral project "Smart management of cultural heritage sites in Italy and China: Earth Observation and pilot projects", we addressed some pioneering investigations to assess multi-mode (multi-band, temporal, resolution) satellite SAR data (including X-band TerraSAR, C-band Envisat and L-band ALOS PALSAR) in archaeological prospection of the Silk road [6]. The Silk Road, a series of trade and cultural transmission routes connecting China to Europe, is the witness of civilization and friendship between the East and West dated back to 2000 years ago, that left us various relics (e.g. lost cities) to be uncovered and investigated.. In particular, the assessment has been performed in the Xinjiang and Gansu section pf the Silk Road focusing on : i) the subsurface penetration capability of SAR data in the arid and semi-arid region ii) and sensitivity of SAR imaging geometry for the detection of relics As regards the point i) , apart from the soil moisture, the penetration is seriously restricted by the soil porosity. For instance, negligible penetration signs were detected in Yumen Frontier Pass either using X- or L-band SAR data due to the occurrence of Yardang landscape. As regards the point ii), the flight path of SAR images in parallel with the

  1. Measuring the Coseismic Displacements of 2010 Ms7.1 Yushu Earthquake by Using SAR and High Resolution Optical Satellite Images

    Science.gov (United States)

    Zhang, L.; Wu, J.; Shi, F.

    2017-09-01

    After the 2010, Mw7.1, Yushu earthquake, many researchers have conducted detail investigations of the surface rupture zone by optical image interpretation, field surveying and inversion of seismic waves. However, how larger of the crustal deformation area caused by the earthquake and the quantitative co-seismic displacements are still not available. In this paper, we first take advantage of D-InSAR, MAI, and optical image matching methods to determine the whole co-seismic displacement fields. Two PALSAR images and two SPOT5 images before and after the earthquake are processed and the co-seismic displacements at the surface rupture zone and far field are obtained. The results are consistent with the field investigations, which illustrates the rationality of the application of optical image matching technology in the earthquake.

  2. The contribution of satellite SAR-derived displacement measurements in landslide risk management practices

    Science.gov (United States)

    Raspini, Federico; Bardi, Federica; Bianchini, Silvia; Ciampalini, Andrea; Del Ventisette, Chiara; Farina, Paolo; Ferrigno, Federica; Solari, Lorenzo; Casagli, Nicola

    2017-04-01

    Landslides are common phenomena that occur worldwide and are a main cause of loss of life and damage to property. The hazards associated with landslides are a challenging concern in many countries, including Italy. With 13% of the territory prone to landslides, Italy is one of the European countries with the highest landslide hazard, and on a worldwide scale, it is second only to Japan among the technologically advanced countries. Over the last 15 years, an increasing number of applications have aimed to demonstrate the applicability of images captured by space-borne Synthetic Aperture Radar (SAR) sensors in slope instability investigations. InSAR (SAR Interferometry) is currently one of the most exploited techniques for the assessment of ground displacements, and it is becoming a consolidated tool for Civil Protection institutions in addressing landslide risk. We present a subset of the results obtained in Italy within the framework of SAR-based programmes and applications intended to test the potential application of C- and X-band satellite interferometry during different Civil Protection activities (namely, prevention, prevision, emergency response and post-emergency phases) performed to manage landslide risk. In all phases, different benefits can be derived from the use of SAR-based measurements, which were demonstrated to be effective in the field of landslide analysis. Analysis of satellite-SAR data is demonstrated to play a major role in the investigation of landslide-related events at different stages, including detection, mapping, monitoring, characterization and prediction. Interferometric approaches are widely consolidated for analysis of slow-moving slope deformations in a variety of environments, and exploitation of the amplitude data in SAR images is a somewhat natural complement for rapid-moving landslides. In addition, we discuss the limitations that still exist and must be overcome in the coming years to manage the transition of satellite SAR

  3. Internal Calibration of HJ-1-C Satellite SAR System

    Directory of Open Access Journals (Sweden)

    Yang Zhen

    2014-06-01

    Full Text Available The HJ-1-C satellite is a Synthetic Aperture Radar (SAR satellite of a small constellation for environmental and disaster monitoring. At present, it is in orbit and working well. The SAR system uses a mesh reflector antenna and centralized power amplifier, and has an internal calibration function in orbit. This study introduces the internal calibration modes and signal paths. The design and realization of the internal calibrator are discussed in detail. Finally, the internal calibration data acquired in orbit are also analyzed.

  4. Ionosphere correction algorithm for spaceborne SAR imaging

    Institute of Scientific and Technical Information of China (English)

    Lin Yang; Mengdao Xing; Guangcai Sun

    2016-01-01

    For spaceborne synthetic aperture radar (SAR) ima-ging, the dispersive ionosphere has significant effects on the pro-pagation of the low frequency (especial y P-band) radar signal. The ionospheric effects can be a significant source of the phase error in the radar signal, which causes a degeneration of the image quality in spaceborne SAR imaging system. The background ionospheric effects on spaceborne SAR through modeling and simulation are analyzed, and the qualitative and quantitative analysis based on the spatio-temporal variability of the ionosphere is given. A novel ionosphere correction algorithm (ICA) is proposed to deal with the ionospheric effects on the low frequency spaceborne SAR radar signal. With the proposed algorithm, the degradation of the image quality caused by the ionosphere is corrected. The simulation re-sults show the effectiveness of the proposed algorithm.

  5. Progress in Circular SAR Imaging Technique

    Directory of Open Access Journals (Sweden)

    Hong Wen

    2012-06-01

    Full Text Available Circular SAR (CSAR is a newly developed all-directional high resolution 3D imaging mode in recent years, to satisfy the demand of finer observation. The National Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences (MITL, IECAS, had the first test flight experiment in Aug. 2011 with a P-band full polarization SAR system, and successfully obtained the all-directional high resolution circular SAR image. The initial results show that CSAR technique has the encouraging potential capability in the fields of high precision mapping, disaster evaluation, resource management and the other related applications. This paper firstly makes a detailed discussion on the progress of circular SAR imaging technique, which emphases on the several airborne experiments performed these years to show CSAR’s attractive features, then studies and illustrates the key techniques, and finally discusses the development trends.

  6. Satellite SAR observation of the sea surface wind field caused by rain cells

    Institute of Scientific and Technical Information of China (English)

    YE Xiaomin; LIN Mingsen; YUAN Xinzhe; DING Jing; XIE Xuetong; ZHANG Yi; XU Ying

    2016-01-01

    Rain cells or convective rain, the dominant form of rain in the tropics and subtropics, can be easy detected by satellite Synthetic Aperture Radar (SAR) images with high horizontal resolution. The footprints of rain cells on SAR images are caused by the scattering and attenuation of the rain drops, as well as the downward airflow. In this study, we extract sea surface wind field and its structure caused by rain cells by using a RADARSAT-2 SAR image with a spatial resolution of 100 m for case study. We extract the sea surface wind speeds from SAR image by using CMOD4 geophysical model function with outside wind directions of NCEP final operational global analysis data, Advance Scatterometer (ASCAT) onboard European MetOp-A satellite and microwave scatterometer onboard Chinese HY-2 satellite, respectively. The root-mean-square errors (RMSE) of these SAR wind speeds, validated against NCEP, ASCAT and HY-2, are 1.48 m/s, 1.64 m/s and 2.14 m/s, respectively. Circular signature patterns with brighter on one side and darker on the opposite side on SAR image are interpreted as the sea surface wind speed (or sea surface roughness) variety caused by downdraft associated with rain cells. The wind speeds taken from the transect profile which superposes to the wind ambient vectors and goes through the center of the circular footprint of rain cell can be fitted as a cosine or sine curve in high linear correlation with the values of no less than 0.80. The background wind speed, the wind speed caused by rain cell and the diameter of footprint of the rain cell with kilometers or tens of kilometers can be acquired by fitting curve. Eight cases interpreted and analyzed in this study all show the same conclusion.

  7. Three-dimensional surface reconstruction from multistatic SAR images.

    Science.gov (United States)

    Rigling, Brian D; Moses, Randolph L

    2005-08-01

    This paper discusses reconstruction of three-dimensional surfaces from multiple bistatic synthetic aperture radar (SAR) images. Techniques for surface reconstruction from multiple monostatic SAR images already exist, including interferometric processing and stereo SAR. We generalize these methods to obtain algorithms for bistatic interferometric SAR and bistatic stereo SAR. We also propose a framework for predicting the performance of our multistatic stereo SAR algorithm, and, from this framework, we suggest a metric for use in planning strategic deployment of multistatic assets.

  8. Optimal Approach to SAR Image Despeckling

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Speckle filtering of synthetic aperture radar (SAR) images while preserving the spatial signal variability (texture and fine structures) still remains a challenge. Many algorithms have been proposed for the SAR imagery despeckling. However,simulated annealing (SA) method is one of excellent choices currently. A critical problem in the study on SA is to provide appropriate cooling schedules that ensure fast convergence to near-optimal solutions. This paper gives a new necessary and sufficient condition for the cooling schedule so that the algorithm state converges in all probability to the set of globally minimum cost states.Moreover, it constructs an appropriate objective function for SAR image despeckling. An experimental result of the actual SAR image processing is obtained.

  9. CFAR Edge Detector for Polarimetric SAR Images

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning; Nielsen, Allan Aasbjerg;

    2003-01-01

    Finding the edges between different regions in an image is one of the fundamental steps of image analysis, and several edge detectors suitable for the special statistics of synthetic aperture radar (SAR) intensity images have previously been developed. In this paper, a new edge detector...

  10. EQUIVALENT BASELINE AND INTERFEROMETRIC PHASE OF CLUSTER SATELLITE SAR

    Institute of Scientific and Technical Information of China (English)

    Gong Min; Zhang Chuanwu; Huang Shunji

    2005-01-01

    The change of the equivalent baseline and interferometric phase of cluster SAR satellites is analyzed when the constellation circles around the Earth and the satellites rotate around the center at the same time. The letter provides assessment of baseline error and phase error which influence the precision of height measurement in the across-track interferometric mode. The mathematical model of cluster satellite movement is built, simulation analyses and the curve of height error are presented. The simulation results show that height measurement error can be compensated by the formulae derived in this letter, therefore, the Digital Elevation Models (DEM's) are recovered accurately.

  11. On Bistatic Forward-looking SAR Imaging

    OpenAIRE

    Vu, Viet Thuy; Pettersson, Mats

    2014-01-01

    Left/right ambiguity and low angular (azimuth) resolution are severe problems for monostatic forward-looking SAR imaging. It is strongly believed that these technical issues can definitely be solved with bistatic forward-looking SAR. The analysis presented in this paper points out that the left/right ambiguity problem still exits. However, an appropriate selection of the position of bistatic base line and antenna beamwidth allows us to conceal it. The paper also gives some recommendations whi...

  12. A modified algorithm for SAR parallel imaging

    Institute of Scientific and Technical Information of China (English)

    HU Ju-rong; WANG Fei; CAO Ning; LU Hao

    2009-01-01

    Synthetic aperture radar can provide two dimension images by converting the acquired echoed SAR signal to targets coordinate and reflectivity. With the advancement of sophisticated SAR signal processing, more and more SAR imaging methods have been proposed for synthetic aperture radar which works at near field and the Fresnel approximation is not appropriate. Time domain correlation is a kind of digital reconstruction method based on processing the synthetic aperture radar data in the two-dimensional frequency domain via Fourier transform. It reconstructs SAR image via simply correlation without any need for approximation or interpolation. But its high computational cost for correlation makes it unsuitable for real time imaging. In order to reduce the computational burden a modified algorithm about time domain correlation was given in this paper. It also can take full advantage of parallel computations of the imaging processor. Its practical implementation was proposed and the preliminary simulation results were presented. Simulation results show that the proposed algorithm is a computationally efficient way of implementing the reconstruction in real time SAR image processing.

  13. Alteration zone Mapping in the Meiduk and Sar Cheshmeh Porphyry Copper Mining Districts of Iran using Advanced Land Imager (ALI Satellite Data

    Directory of Open Access Journals (Sweden)

    A. Beiranvand Pour

    2015-10-01

    Full Text Available This study evaluates the capability of Earth Observing-1 (EO1 Advanced Land Imager (ALI data for hydrothermal alteration mapping in the Meiduk and Sar Cheshmeh porphyry copper mining districts, SE Iran. Feature-oriented principal components selection, 4/2, 8/9, 5/4 band ratioing were applied to ALI data for enhancing the hydrothermally altered rocks associated with porphyry copper mineralization, lithological units and vegetation. Mixture-tuned matched-filtering (MTMF was tested to discriminate the hydrothermal alteration areas of porphyry copper mineralization from surrounding environment using the shortwave infrared bands of ALI. Results indicate that the tested methods are able to yield spectral information for identifying vegetation, iron oxide/hydroxide and clay minerals, lithological units and the discrimination of hydrothermally altered rocks from unaltered rocks using ALI data.

  14. Alteration zone Mapping in the Meiduk and Sar Cheshmeh Porphyry Copper Mining Districts of Iran using Advanced Land Imager (ALI) Satellite Data

    Science.gov (United States)

    Beiranvand Pour, A.; Hashim, M.

    2015-10-01

    This study evaluates the capability of Earth Observing-1 (EO1) Advanced Land Imager (ALI) data for hydrothermal alteration mapping in the Meiduk and Sar Cheshmeh porphyry copper mining districts, SE Iran. Feature-oriented principal components selection, 4/2, 8/9, 5/4 band ratioing were applied to ALI data for enhancing the hydrothermally altered rocks associated with porphyry copper mineralization, lithological units and vegetation. Mixture-tuned matched-filtering (MTMF) was tested to discriminate the hydrothermal alteration areas of porphyry copper mineralization from surrounding environment using the shortwave infrared bands of ALI. Results indicate that the tested methods are able to yield spectral information for identifying vegetation, iron oxide/hydroxide and clay minerals, lithological units and the discrimination of hydrothermally altered rocks from unaltered rocks using ALI data.

  15. An Advanced Rotation Invariant Descriptor for SAR Image Registration

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2017-07-01

    Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

  16. Estimating IMU heading error from SAR images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2009-03-01

    Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.

  17. Geo-correction Algorithm Based on Equivalent RD Model for ScanSAR of HJ-1-C Satellite

    OpenAIRE

    Liu Jia-yin; Wen Shuang-yan; Zhang Hong-yi; Hong Wen

    2014-01-01

    HJ-1-C satellite is the first Synthetic Aperture Radar (SAR) satellite for civilian use in China, and it has a strip and scan mode. According to the characteristics of the ScanSAR of the HJ-1-C satellite, a geo-correction algorithm based on an equivalent RD model has been outlined in this paper on the basis of an ECS image processing algorithm and a traditional Range-Doppler location method. An azimuth mosaic was presented by a time series relationship, then the different burst was stitched b...

  18. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross sections...... of the object using a CAD-model. The raw measurements are input to a SAR system and terrain model, which models thermal noise, terrain clutter, and SAR focusing to produce synthetic SAR images. Examples of SAR images at 0.3m and 0.1m resolution, and a comparison with real SAR imagery from the MSTAR dataset...

  19. Fast SAR Imaging Algorithm for FLGPR

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A fast SAR imaging algorithm for near- field subsurface forward-looking ground penetrating radar (FLGPR) is presented. By using nonstationary convolution filter, the refocused image spectrum can be reconstructed directly from the backscattered signal spectrum of target area. The experimental results show the proposed method can fast achieve image refocusing. Also it has higher computational efficiency than the phase-shift migration approach and the delay-and-sum (DAS) approach.

  20. MAPSAR Image Simulation Based on L-band Polarimetric Data from the SAR-R99B Airborne Sensor (SIVAM System

    Directory of Open Access Journals (Sweden)

    Wagner Fernando da Silva

    2009-01-01

    Full Text Available This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR satellite from the airborne SAR R99B sensor (SIVAM System. MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research and DLR (German Aerospace Center targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed.

  1. Multichannel imaging with the AMBER FMCW SAR

    NARCIS (Netherlands)

    Otten, M.P.G.; Rossum, W.L. van; Graaf, M.W. van der; Vlothuizen, W.J.; Tan, R.G.

    2014-01-01

    An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to achieve low power and advanced imaging SAR capabilities on small platform

  2. Multichannel imaging with the AMBER FMCW SAR

    NARCIS (Netherlands)

    Otten, M.P.G.; Rossum, W.L. van; Graaf, M.W. van der; Vlothuizen, W.J.; Tan, R.G.

    2014-01-01

    An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to achieve low power and advanced imaging SAR capabilities on small platform

  3. Multichannel imaging with the AMBER FMCW SAR

    NARCIS (Netherlands)

    Otten, M.P.G.; Rossum, W.L. van; Graaf, M.W. van der; Vlothuizen, W.J.; Tan, R.G.

    2014-01-01

    An X-band Digital Array Synthetic Aperture Radar for a Short Range Tactical UAV is presented. The Frequency Modulated Continuous Wave radar principle in combination with digital beam forming over 24 receive channels is used to achieve low power and advanced imaging SAR capabilities on small

  4. System Design and In-orbit Verification of the HJ-1-C SAR Satellite

    OpenAIRE

    Zhang Run-ning; Jiang Xiu-peng

    2014-01-01

    HJ-1-C is a SAR satellite owned by the Chinese Environment and Natural Disaster Monitoring constellation, and works together with the optical satellites HJ-1-A/B for monitoring environment and natural disasters. In this paper, the system design and characteristics of the first Chinese civil SAR satellite are described. In addition, the interface relation between SAR payload and platform is studied. Meanwhile, the data transmission capability, attitude, power, and temperature control that supp...

  5. ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. W. Zhao

    2016-06-01

    Full Text Available As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings and the physical parameters of the surface (roughness, correlation length, permittivitywhich determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  6. ALGORITHM OF SAR SATELLITE ATTITUDE MEASUREMENT USING GPS AIDED BY KINEMATIC VECTOR

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper, in order to improve the accuracy of the Synthetic Aperture Radar (SAR)satellite attitude using Global Positioning System (GPS) wide-band carrier phase, the SAR satellite attitude kinematic vector and Kalman filter are introduced. Introducing the state variable function of GPS attitude determination algorithm in SAR satellite by means of kinematic vector and describing the observation function by the GPS wide-band carrier phase, the paper uses the Kalman filter algorithm to obtian the attitude variables of SAR satellite. Compared the simulation results of Kalman filter algorithm with the least square algorithm and explicit solution, it is indicated that the Kalman filter algorithm is the best.

  7. InSAR Forensics: Tracing InSAR Scatterers in High Resolution Optical Image

    Science.gov (United States)

    Wang, Yuanyuan; Zhu, XiaoXiang

    2015-05-01

    This paper presents a step towards a better interpretation of the scattering mechanism of different objects and their deformation histories in SAR interferometry (InSAR). The proposed technique traces individual SAR scatterer in high resolution optical images where their geometries, materials, and other properties can be better analyzed and classified. And hence scatterers of a same object can be analyzed in group, which brings us to a new level of InSAR deformation monitoring.

  8. SAR-SIFT: A SIFT-LIKE ALGORITHM FOR SAR IMAGES

    OpenAIRE

    Dellinger, Flora; Delon, Julie; Gousseau, Yann; Michel, Julien; Tupin, Florence

    2015-01-01

    International audience; The Scale Invariant Feature Transform (SIFT) algorithm is widely used in computer vision to match features between images or to localize and recognize objets. However, mostly because of speckle noise, it does not perform well on synthetic aperture radar (SAR) images. We present here an improvement of this algorithm for SAR images, named SAR-SIFT. A new gradient computation, yielding an orientation and a magnitude robust to speckle noise, is first introduced. It is then...

  9. Non-parametric partitioning of SAR images

    Science.gov (United States)

    Delyon, G.; Galland, F.; Réfrégier, Ph.

    2006-09-01

    We describe and analyse a generalization of a parametric segmentation technique adapted to Gamma distributed SAR images to a simple non parametric noise model. The partition is obtained by minimizing the stochastic complexity of a quantized version on Q levels of the SAR image and lead to a criterion without parameters to be tuned by the user. We analyse the reliability of the proposed approach on synthetic images. The quality of the obtained partition will be studied for different possible strategies. In particular, one will discuss the reliability of the proposed optimization procedure. Finally, we will precisely study the performance of the proposed approach in comparison with the statistical parametric technique adapted to Gamma noise. These studies will be led by analyzing the number of misclassified pixels, the standard Hausdorff distance and the number of estimated regions.

  10. The impact of curved satellite tracks on SAR focusing

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2000-01-01

    This paper addresses the geometric effect of processing single look complex synthetic aperture radar (SAR) data to a reference squint angle different from that given by the center of the real antenna beam. For data acquired on a straight flight line, the required transformation of radar coordinates...... from one Doppler reference to another is independent of the target elevation but for data acquired from a satellite orbit over a rotating Earth that is not true. Also the effect of ignoring Earth rotation is addressed....

  11. SAR Image Texture Analysis of Oil Spill

    Science.gov (United States)

    Ma, Long; Li, Ying; Liu, Yu

    Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they have serious affect on fragile marine and coastal ecosystem. In order to implement an emergency in case of oil spills, it is necessary to monitor oil spill using remote sensing. Spaceborne SAR is considered a promising method to monitor oil spill, which causes attention from many researchers. However, research in SAR image texture analysis of oil spill is rarely reported. On 7 December 2007, a crane-carrying barge hit the Hong Kong-registered tanker "Hebei Spirit", which released an estimated 10,500 metric tons of crude oil into the sea. The texture features on this oil spill were acquired based on extracted GLCM (Grey Level Co-occurrence Matrix) by using SAR as data source. The affected area was extracted successfully after evaluating capabilities of different texture features to monitor the oil spill. The results revealed that the texture is an important feature for oil spill monitoring. Key words: oil spill, texture analysis, SAR

  12. Unparallel trajectory bistatic spotlight SAR imaging

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; JING Wei; XING MengDao; BAO Zheng

    2009-01-01

    A new approach for unparallel trajectory bistatic spotlight SAR imaging is proposed. The approach utilizes the concept of instantaneous Doppler wavenumber and introduces two variants, the sum-range and subtraction-range, to develop the 2D frequency analytical formula. Based on the assumption of plane wavefront, the transmitting and receiving Doppler are separated and formulated via series reversion. And frequency scaling is applied to focus image. The algorithm is with high computational efficiency, and provides well focus for limited scene imaging. Simulation result confirms the validity of the approach.

  13. Preliminary Analysis of a Novel SAR Based Emergency System for Earth Orbit Satellites using Galileo

    NARCIS (Netherlands)

    Gill, E.K.A.; Helderweirt, A.

    2010-01-01

    This paper presents a preliminary analysis of a novel Search and Rescue (SAR) based emergency system for Low Earth Orbit (LEO) satellites using the Galileo Global Navigation Satellite System (GNSS). It starts with a description of the space user SAR system including a concept description, mission ar

  14. Coastline detection in SAR images using discriminant cuts segmentation

    Science.gov (United States)

    Ding, Xianwen; Zou, Xiaolin; Yu, Tan

    2016-11-01

    The discriminant cut algorithm is used to detect coastlines in synthetic aperture radar (SAR) images. The proposed approach is a region-based one, which is able to capture and utilize spatial information in the image. The real SAR images, e.g. ALOS-1 PALSAR and COSMO-SkyMed SAR images, together with in-situ GPS data were collected and used to validate the performance of the proposed approach for coastline detection in SAR images. The accuracy is better than 4 times the image resolution. The efficiency is also tested.

  15. Complementing geotechnical slope stability and land movement analysis using satellite DInSAR

    Science.gov (United States)

    Tripolitsiotis, Achilleas; Steiakakis, Chrysanthos; Papadaki, Eirini; Agioutantis, Zacharias; Mertikas, Stelios; Partsinevelos, Panagiotis

    2014-03-01

    This paper explores the potential of using satellite radar inteferometry to monitor time-varying land movement prior to any visible tension crack signs. The idea was developed during dedicated geotechnical studies at a large open-pit lignite mine, where large slope movements (10-20 mm/day) were monitored and large fissures were observed in the immediate area outside the current pit limits. In this work, differential interferometry (DInSAR), using Synthetic Aperture Radar (SAR) ALOS images, was applied to monitor the progression of land movement that could potentially thwart mine operations. Early signs of land movements were captured by this technique well before their visual observation. Moreover, a qualitative comparison of DInSAR and ground geodetic measurements indicates that the technique can be used for the identification of high risk areas and, subsequently, for the optimization of the spatial distribution of the available ground monitoring equipment. Finally, quantitative land movement results from DInSAR are shown to be in accordance with simultaneous measurements obtained by ground means.

  16. The first Sentinel-1 SAR image of a typhoon

    Institute of Scientific and Technical Information of China (English)

    LI Xiaofeng

    2015-01-01

    In this note, we present the first Sentinel-1 synthetic aperture radar (SAR) typhoon image acquired in the northwest Pacific on October 4, 2014. The eye shape and sea surface wind patterns associated with Typhoon Phanfone are clearly shown in the high-quality SAR image. SAR winds retrieval procedure was given but the actual wind estimates will only be available after the European Space Agency (ESA) releases the official calibration coefficients in order to accurately derive the SAR-measured normalized radar cross section. This study demonstrates the advantage of Sentinel-1 SAR with regards to imaging fine scale typhoon patterns on the sea surface beneath storm clouds. This paper also advocates the use of Sentinel-1 SAR data that is made freely and openly available worldwide for the first time in civilian SAR history.

  17. SAR-PC: Edge Detection in SAR Images via an Advanced Phase Congruency Model

    Directory of Open Access Journals (Sweden)

    Yuming Xiang

    2017-02-01

    Full Text Available Edge detection in Synthetic Aperture Radar (SAR images has been a challenging task due to the speckle noise. Ratio-based edge detectors are robust operators for SAR images that provide constant false alarm rates, but they are only optimal for step edges. Edge detectors developed by the phase congruency model provide the identification of different types of edge features, but they suffer from speckle noise. By combining the advantages of the two edge detectors, we propose a SAR phase congruency detector (SAR-PC. Firstly, an improved local energy model for SAR images is obtained by replacing the convolution of raw image and the quadrature filters by the ratio responses. Secondly, a new noise level is estimated for the multiplicative noise. Substituting the SAR local energy and the new noise level into the phase congruency model, SAR-PC is derived. Edge response corresponds to the max moment of SAR-PC. We compare the proposed detector with the ratio-based edge detectors and the phase congruency edge detectors. Receiver Operating Characteristic (ROC curves and visual effects are used to evaluate the performance. Experimental results of simulated images and real-world images show that the proposed edge detector is robust to speckle noise and it provides a consecutive edge response.

  18. Detection of wind wakes offshore from satellite SAR

    Science.gov (United States)

    Christiansen, M. B.; Hasager, C. B.

    A study is presented on the mapping of ocean wind fields for detection of wind wakes downstream of an offshore wind farm. The study is based on ERS-2 Synthetic Aperture Radar (SAR) scenes obtained in 2003 over Horns Reef in the North Sea. A large offshore wind farm (80 wind turbines) is located 14-20 km offshore of Denmark on this submerged reef. Meteorological observations are available from an offshore mast; wind speed is measured at four heights up to 62 m and wind direction is measured at 60 m. Maps of wind speed are generated from geophysical model functions (CMOD-4, CMOD-IFR2) with a resolution of 400 m by 400 m using wind direction obtained from in-situ measurements as model input. The wind maps display zones of reduced mean wind speed downstream of the wind farm compared to upwind conditions. The reduction is approximately 10 % immediately behind the wind farm and the wake effect is vanishing over distances in the order of 10 km downstream. This is consistent with wake model predictions. Satellite SAR provides a good estimate of the propagation of wind wakes. Information on how structures affect the local wind climate is useful for wind energy purposes, particularly for siting of future offshore wind farms.

  19. First Image Products from EcoSAR - Osa Peninsula, Costa Rica

    Science.gov (United States)

    Osmanoglu, Batuhan; Lee, SeungKuk; Rincon, Rafael; Fatuyinbo, Lola; Bollian, Tobias; Ranson, Jon

    2016-01-01

    Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

  20. Validation of satellite SAR offshore wind speed maps to in-situ data, microscala and mesoscale model results

    Energy Technology Data Exchange (ETDEWEB)

    Hasager, C.B.; Astrup, P.; Barthelmie, R.; Dellwik, E.; Hoffmann Joergensen, B.; Gylling Mortensen, N.; Nielsen, M.; Pryor, S.; Rathmann, O.

    2002-05-01

    captured the local wind speeds very well especially near the coast and up to around 5 km offshore. Further offshore the KAMM2 model results seemed more reliable than the WAsP model. This is likely due to the effect of high orography of the island Corsica located North of the study area. The mountains were included in the KAMM2 model domain but not in the WAsP model domain. The mountains had a significant impact on the wind field far offshore. In the Gulf of Suez the winds are very strong but there exists large spatial wind speed gradients and this makes the site challenging for SAR wind speed validation studies. Only three cases were analyzed for the Gulf of Suez in Egypt. A study on how many wind speed maps would be needed for wind resource estimation showed that around 60-70 randomly selected satellite images are required to characterize the mean wind speed and Weibull c parameter, while of the order of 150 images are required to obtain a variance estimate, and nearly 2000 are needed to obtain a robust estimate of energy density (or Weibull k). This is under the assumption of no error in the SAR wind speed maps and for an uncertainty of {+-} 10% at a confidence level of 90%. Around 100 satellite SAR scenes may be available for some sites on Earth but far few at other sites. Currently the number of available satellite SAR scenes is increasing rapidly with ERS-2, RADARSAT-1 and ENVISAT in orbit. Hence the technique holds promise for future utilization in offshore wind resource assessment. (au)

  1. Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern

    Science.gov (United States)

    Doerry, Armin W.

    2013-04-30

    Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.

  2. An Optical Flow Method Applied to Co-Registration of Remote Sensing Images: Example for SAR/SAR, SAR/LIDAR, SAR/Optical Images of BIOSAR 2010 Campaign

    Science.gov (United States)

    Colin-Koeniguer, Elise

    2016-08-01

    This article proposes an optical flow type method for coregistration of forest remote sensing images. The principle of the algorithm called GeFolki is first explained. Results are shown on the images of the BioSAR 3 campaign, for the production of SAR interferograms, the coregistration a SAR and LIDAR image, and the coregistration an optical image and SAR image.The advantages of such an algorithm over conventional algorithms are explained. Finally, we propose various applications within the operating data for future BIOMASS mission: massive interferometry, ground truth production, upscaling by fusion of LIDAR and SAR data, and image mining.

  3. Fast terrain modelling for hydrogeological risk mapping and emergency management: the contribution of high-resolution satellite SAR imagery

    Directory of Open Access Journals (Sweden)

    A. Nascetti

    2015-07-01

    Full Text Available Geomatic tools fast terrain modelling play a relevant role in hydrogeological risk mapping and emergency management. Given their complete independence from logistic constraints on the ground (as for airborne data collection, illumination (daylight, and weather (clouds conditions, synthetic aperture radar (SAR satellite systems may provide important contributions in terms of digital surface models (DSMs and digital elevation models (DEMs. For this work we focused on the potential of high-resolution SAR satellite imagery for DSM generation using an interferometric (InSAR technique and using a revitalized radargrammetric stereomapping approach. The goal of this work was just methodological. Our goal was to illustrate both the fundamental advantages and drawbacks of the radargrammetric approach with respect to the InSAR technique for DSM generation, and to outline their possible joint role in hydrogeological risk mapping and emergency management. Here, it is worth mentioning that radargrammetry procedures are independent of image coherence (unlike the interferometric approach and phase unwrapping, as well as of parsimony (only a few images are necessary. Therefore, a short time is required for image collection (from tens of minutes to a few hours, thanks to the independence from illumination and weather. The most relevant obstacles of the technique are speckle and the lack of texture impact on image matching, as well as the well-known deformations of SAR imagery (layover and foreshortening, which may produce remarkable difficulties with complex morphologies and that must be accounted for during acquisition planning. Here, we discuss results obtained with InSAR and radargrammetry applied to a COSMO-SkyMed SpotLight triplet (two stereopairs suited for radargrammetry and InSAR, sharing one common image acquired over suburbs of San Francisco (United States, which are characterized by mixed morphology and land cover. We mainly focused on urban areas and

  4. 星/机双站SAR成像处理技术研究%Bistatic SAR Imaging for Satellite/Airborne Configuration

    Institute of Scientific and Technical Information of China (English)

    李建阳; 常文革

    2010-01-01

    针对发射机为卫星、接收机为载机且飞行航迹平行模式下的双站SAR,本文建立了网波信号的模型,分析了多普勒调频率、多普勒中心、目标位置、距离弯曲等参数的变化;采用单站SAR等效法推导了回波信号二维频谱,并对单站SAR等效法与距离历程泰勒级数展开法所产生的相位误差进行了比较,进而采用Nonlinear Chirp Scaling(NCS)算法进行成像处理.通过插值校正目标沿方位向出现的几何拉伸形变,采用距离频谱搬移校正目标沿距离向的几何偏差.最后,采用仿真数据验证了本文方法的正确性.

  5. Speckle Suppression Method for SAR Image

    Directory of Open Access Journals (Sweden)

    Jiming Guo

    2013-04-01

    Full Text Available In this study, a new speckle reduction method was proposed in terms of by Bidimensional Empirical Mode Decomposition (BEMD. In this method, the SAR image containing speckle noise was decomposed into a number of elementary components by using BEMD and then the extremal points are done the boundary equivalent extension after screening and the residual continue to be done the boundary equivalent extension until screening is completed, finally, the image was reconstructed, which reduced the speckle noise. Experimental results show that this method has good effect on suppressing speckle noise, compared to the average filter, median filter and gaussian filter and has advantages of sufficiently retaining edge and detail information while suppressing speckle noise.

  6. SAR Image Desp eckling by Sparse Reconstruction Based on Shearlets

    Institute of Scientific and Technical Information of China (English)

    JI Jian; LI Xiao; XU Shuang-Xing; LIU Huan; HUANG Jing-Jing

    2015-01-01

    Synthetic aperture radar (SAR) image is usually polluted by multiplicative speckle noise, which can affect further processing of SAR image. This paper presents a new approach for multiplicative noise removal in SAR images based on sparse coding by shearlets filtering. First, a SAR despeckling model is built by the theory of compressed sensing (CS). Secondly, obtain shearlets coefficient through shearlet transform, each scale coefficient is represented as a unit. For each unit, sparse coefficient is iteratively estimated by using Bayesian estimation based on shearlets domain. The represented units are finally collaboratively aggregated to construct the despeckling image. Our results in SAR image despeckling show the good performance of this algorithm, and prove that the algorithm proposed is robustness to noise, which is not only good for reducing speckle, but also has an advantage in holding information of the edge.

  7. Wave observation in the marginal ice zone with the TerraSAR-X satellite

    Science.gov (United States)

    Gebhardt, Claus; Bidlot, Jean-Raymond; Gemmrich, Johannes; Lehner, Susanne; Pleskachevsky, Andrey; Rosenthal, Wolfgang

    2016-07-01

    This article investigates the penetration of ocean waves into the marginal ice zone (MIZ), observed by satellite, and likewise provides a basis for the future cross-validation of respective models. To this end, synthetic aperture radar images from the TerraSAR-X satellite (TS-X) and numerical simulations of the European Centre for Medium-Range Weather Forecasts (ECMWF) are used. The focus is an event of swell waves, developed during a storm passage in the Atlantic, penetrating deeply into the MIZ off the coast of Eastern Greenland in February 2013. The TS-X scene which is the basis for this investigation extends from the ice-free open ocean to solid ice. The variation of the peak wavelength is analysed and potential sources of variability are discussed. We find an increase in wavelength which is consistent with the spatial dispersion of deep water waves, even within the ice-covered region.

  8. Monitoring and characterizing natural hazards with satellite InSAR imagery

    Science.gov (United States)

    Lu, Zhong; Zhang, Jixian; Zhang, Yonghong; Dzurisin, Daniel

    2010-01-01

    Interferometric synthetic aperture radar (InSAR) provides an all-weather imaging capability for measuring ground-surface deformation and inferring changes in land surface characteristics. InSAR enables scientists to monitor and characterize hazards posed by volcanic, seismic, and hydrogeologic processes, by landslides and wildfires, and by human activities such as mining and fluid extraction or injection. Measuring how a volcano’s surface deforms before, during, and after eruptions provides essential information about magma dynamics and a basis for mitigating volcanic hazards. Measuring spatial and temporal patterns of surface deformation in seismically active regions is extraordinarily useful for understanding rupture dynamics and estimating seismic risks. Measuring how landslides develop and activate is a prerequisite to minimizing associated hazards. Mapping surface subsidence or uplift related to extraction or injection of fluids during exploitation of groundwater aquifers or petroleum reservoirs provides fundamental data on aquifer or reservoir properties and improves our ability to mitigate undesired consequences. Monitoring dynamic water-level changes in wetlands improves hydrological modeling predictions and the assessment of future flood impacts. In addition, InSAR imagery can provide near-real-time estimates of fire scar extents and fire severity for wildfire management and control. All-weather satellite radar imagery is critical for studying various natural processes and is playing an increasingly important role in understanding and forecasting natural hazards.

  9. A beamforming algorithm for bistatic SAR image formation.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David Alan; Wahl, Daniel Eugene; Jakowatz, Charles V., Jr.

    2010-03-01

    Beamforming is a methodology for collection-mode-independent SAR image formation. It is essentially equivalent to backprojection. The authors have in previous papers developed this idea and discussed the advantages and disadvantages of the approach to monostatic SAR image formation vis--vis the more standard and time-tested polar formatting algorithm (PFA). In this paper we show that beamforming for bistatic SAR imaging leads again to a very simple image formation algorithm that requires a minimal number of lines of code and that allows the image to be directly formed onto a three-dimensional surface model, thus automatically creating an orthorectified image. The same disadvantage of beamforming applied to monostatic SAR imaging applies to the bistatic case, however, in that the execution time for the beamforming algorithm is quite long compared to that of PFA. Fast versions of beamforming do exist to help alleviate this issue. Results of image reconstructions from phase history data are presented.

  10. A beamforming algorithm for bistatic SAR image formation

    Science.gov (United States)

    Jakowatz, Charles V., Jr.; Wahl, Daniel E.; Yocky, David A.

    2010-04-01

    Beamforming is a methodology for collection-mode-independent SAR image formation. It is essentially equivalent to backprojection. The authors have in previous papers developed this idea and discussed the advantages and disadvantages of the approach to monostatic SAR image formation vis-à-vis the more standard and time-tested polar formatting algorithm (PFA). In this paper we show that beamforming for bistatic SAR imaging leads again to a very simple image formation algorithm that requires a minimal number of lines of code and that allows the image to be directly formed onto a three-dimensional surface model, thus automatically creating an orthorectified image. The same disadvantage of beamforming applied to monostatic SAR imaging applies to the bistatic case, however, in that the execution time for the beamforming algorithm is quite long compared to that of PFA. Fast versions of beamforming do exist to help alleviate this issue. Results of image reconstructions from phase history data are presented.

  11. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  12. Investigation on Fine Registration for SAR and Optical Image

    Directory of Open Access Journals (Sweden)

    You Hong-jian

    2014-02-01

    Full Text Available The registration of SAR and optical remote sensing image is the basise for fusing of multi-source image and comprehensive analysis. In this paper a new fine registration method for SAR and optical image is proposed. Firstly, three to four corresponding points are selected manually to realize a coarse registration that eliminates the differences in scale and rotation. Many characteristic points in the optical image are detected and the corresponding points in SAR image are extracted using normalized gradient correlations based on the different gradients by operators. An irregular triangle network is constructed using these corresponding points and each triangle region is finely registered. Finally SAR image and optical image are finely registered. Experiment and processed results demonstrate the feasibility of this method.

  13. Fusion of Spaceborne Optical and SAR Images for Building Height Quick Extraction in Big Urban Areas

    Directory of Open Access Journals (Sweden)

    TIAN Feng

    2017-07-01

    Full Text Available The spaceborne high-resolution optical images and synthetic aperture radar (SAR images are applied to extract building height in urban areas widely. But the lack of optical satellite parameters along with the SAR images' incomplete scattering characteristics and inefficient extraction make the application flawed. To cure the above problems, we investigated the joint use of the spaceborne high-resolution optical images and SAR images to extract building height information quickly in big urban areas. The chain is decomposed into the main following steps: First, the building shadows are extracted by integrating support vector machines (SVM with morphological shadow index (MSI and their lengths are measured automatically. Then, the height extraction from SAR images based on a model matching technique for some appropriate samples. Finally, obtain the other heights based on the simple linear regression analysis. This approach which combines the data and feature from different satellite systems to make up the flaws for each other is not only efficient and low-cost, but also satisfy the basic accuracy requirement.

  14. Wind mapping offshore in coastal Mediterranean area using SAR images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...... of missing data. Here, we focus on evaluating the use of SAR for offshore wind mapping. Preliminary results from the analysis of SAR-based ocean winds in Mediterranean areas show interesting large scale wind flow features consistent with results from previous studies using numerical models and space borne...

  15. Offshore Wind Resource Estimation in Mediterranean Area Using SAR Images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...... of missing data. Here, we focus on evaluating the use of SAR for offshore wind mapping. Preliminary results from the analysis of SAR-based ocean winds in Mediterranean areas show interesting large scale wind flow features consistent with results from previous studies using numerical models and space borne...

  16. SAR IMAGING SIMULATION OF HORIZONTAL FULLY TWO-DIMENSIONAL INTERNAL WAVES

    Institute of Scientific and Technical Information of China (English)

    SHEN Hui; HE Yi-Jun

    2006-01-01

    Based on the research of Lynett and Liu, a new horizontal fully two-dimensional internal wave propagation model with rotation effect was deduced, which can be used to simulate the characteristics of internal waves in a horizontal fully two-dimensional plane. By combining the imaging mechanism of Synthetic Aperture Radar(SAR), a simulation procedure was fatherly acquired, which can simulate the propagation characteristics of oceanic internal waves into SAR images. In order to evaluate the validity of the proposed simulation procedure, case studies are performed in South China Sea and results from simulation procedure are analyzed in detail. A very good consistency was found between the simulation results and satellite images. The proposed simulation procedure will be a possible foundation for the quantitative interpretation of internal waves from fully two-dimensional satellite images.

  17. The ONERA Airborne Multi Frequency SAR Imaging Systems (PREPRINT)

    Science.gov (United States)

    2014-10-09

    The ONERA Airborne Multi-Frequency SAR Imaging Systems Olivier Ruault du Plessis Electromagnetism and Radar Department ONERA Salon de...Provence FRANCE Olivier.Ruault_du_Plessis@onera.fr Philippe Dreuillet Electromagnetism and Radar Department ONERA Palaiseau FRANCE...Philippe.Dreuillet@onera.fr Abstract—RAMSES-NG and SETHI, the airborne SAR systems developed by ONERA , integrate new generation of radar and optronics

  18. Classification of Targets in SAR Images Using ISAR Data

    NARCIS (Netherlands)

    Wit, J.J.M. de; Dekker, R.J.; Broek, A.C. van den

    2005-01-01

    Feature-based classification of targets in SAR images by using ISAR measurements was studied, based on polarimetric SAR and ISAR data acquired with the MEMPHIS radar system of FGAN-FHR. The data contained one T-72 battle tank, one BMP combat vehicle, and several confusers. The resolution was 75 cm.

  19. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus

    2017-03-01

    Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU

  20. Governance from space: Satellite InSAR observations to support decision-making and to avoid calamities

    Science.gov (United States)

    Lambert, John; De Lange, Ger; Maccabiani, Jos

    2014-05-01

    Satellites are revolving around the earth already for over five decades, nowadays allowing us to have images of every location on our planet, using different techniques. These images are used for many different purposes, but the number of applications is still growing fast. In this paper, some practical applications of InSAR (Interferometric Synthetic Aperture Radar) data are described. The detection of trends in the movements of the earth surface and those of buildings and infrastructure is one of the applications for this infrastructure. InSAR data from the North-East Groningen gas field region show how large scale subsidence patterns can be detected and can support spatial planning strategies. Another case, in Diemen, shows how InSAR data support the municipal government in their management strategies. Another case shows how InSAR observations, taken from the entrance to the Vlaketunnel, could have warned in advance for the collapse of one of these entries. Finally, it will be shown that InSAR data can be helpful to monitor the effects of (underground) civil engineering activities, such as the construction of the North-Southline in Amsterdam.

  1. Research on Airborne SAR Imaging Based on Esc Algorithm

    Science.gov (United States)

    Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.

    2017-09-01

    Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  2. Multi-look polarimetric SAR image filtering using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper

    2000-01-01

    Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...... matrices, and by applying a set of small orientation-dependent filters in an iterative scheme, the input image becomes highly filtered while maintaining most of the structures in the scene. Results using multi-look polarimetric C-band data from the Danish airborne polarimetric SAR, EMISAR, are presented....

  3. SAR image effects on coherence and coherence estimation.

    Energy Technology Data Exchange (ETDEWEB)

    Bickel, Douglas Lloyd

    2014-01-01

    Radar coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.

  4. Refocusing of Moving Targets in SAR Images via Parametric Sparse Representation

    Directory of Open Access Journals (Sweden)

    Yichang Chen

    2017-08-01

    Full Text Available In this paper, a parametric sparse representation (PSR method is proposed for refocusing of moving targets in synthetic aperture radar (SAR images. In regular SAR images, moving targets are defocused due to unknown motion parameters. Refocusing of moving targets requires accurate phase compensation of echo data. In the proposed method, the region of interest (ROI data containing the moving targets are extracted from the complex SAR image and represented in a sparse fashion through a parametric transform, which is related to the phase compensation parameter. By updating the reflectivities of moving target scatterers and the parametric transform in an iterative fashion, the phase compensation parameter can be accurately estimated and the SAR images of moving targets can be refocused well. The proposed method directly operates on small-size defocused ROI data, which helps to reduce the computational burden and suppress the clutter. Compared to other existing ROI-based methods, the proposed method can suppress asymmetric side-lobes and improve the image quality. Both simulated data and real SAR data collected by GF-3 satellite are used to validate the effectiveness of the proposed method.

  5. Fast correlation technique for glacier flow monitoring by digital camera and space-borne SAR images

    Directory of Open Access Journals (Sweden)

    Moreau Luc

    2011-01-01

    Full Text Available Abstract Most of the image processing techniques have been first proposed and developed on small size images and progressively applied to larger and larger data sets resulting from new sensors and application requirements. In geosciences, digital cameras and remote sensing images can be used to monitor glaciers and to measure their surface velocity by different techniques. However, the image size and the number of acquisitions to be processed to analyze time series become a critical issue to derive displacement fields by the conventional correlation technique. In this paper, a mathematical optimization of the classical normalized cross-correlation and its implementation are described to overcome the computation time and window size limitations. The proposed implementation is performed with a specific memory management to avoid most of the temporary result re-computations. The performances of the software resulting from this optimization are assessed by computing the correlation between optical images of a serac fall, and between Synthetic Aperture Radar (SAR images of Alpine glaciers. The optical images are acquired by a digital camera installed near the Argentière glacier (Chamonix, France and the SAR images are acquired by the high resolution TerraSAR-X satellite over the Mont-Blanc area. The results illustrate the potential of this implementation to derive dense displacement fields with a computational time compatible with the camera images acquired every 2 h and with the size of the TerraSAR-X scenes covering 30 × 50 km2.

  6. Road network extraction in classified SAR images using genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    肖志强; 鲍光淑; 蒋晓确

    2004-01-01

    Due to the complicated background of objectives and speckle noise, it is almost impossible to extract roads directly from original synthetic aperture radar(SAR) images. A method is proposed for extraction of road network from high-resolution SAR image. Firstly, fuzzy C means is used to classify the filtered SAR image unsupervisedly, and the road pixels are isolated from the image to simplify the extraction of road network. Secondly, according to the features of roads and the membership of pixels to roads, a road model is constructed, which can reduce the extraction of road network to searching globally optimization continuous curves which pass some seed points. Finally, regarding the curves as individuals and coding a chromosome using integer code of variance relative to coordinates, the genetic operations are used to search global optimization roads. The experimental results show that the algorithm can effectively extract road network from high-resolution SAR images.

  7. Speckle filtering in satellite SAR change detection imagery

    NARCIS (Netherlands)

    Dekker, R.J.

    1998-01-01

    Repeat-pass Synthetic Aperture Radar (SAR) imagery is useful for change detection. A disadvantage of SAR is the system-inherent speckle noise. This can be reduced by filtering. Various filter types and methods are described in the literature, but not one fits the speckle noise in change detection

  8. Analysis of Benefits and Pitfalls of Satellite SAR for Coastal Area Monitoring

    Science.gov (United States)

    Nunziata, F.; Buono, A.; Mgliaccio, M.; Li, X.; Wei, Y.

    2016-08-01

    This study aims at describing the outcomes of the Dragon-3 project no. 10689. The undertaken activities deal with coastal area monitoring and they include sea pollution and coastline extraction. The key remote sensing tool is the Synthetic Aperture Radar (SAR) that provides fine resolution images of the microwave reflectivity of the observed scene. However, the interpretation of SAR images is not at all straightforward and all the above-mentioned coastal area applications cannot be easily addressed using single-polarization SAR. Hence, the main outcome of this project is investigating the capability of multi-polarization SAR measurements to generate added-vale product in the frame of coastal area management.

  9. SAR Imaging of Moving Targets via Compressive Sensing

    CERN Document Server

    Wang, Jun; Zhang, Hao; Wang, Xiqin

    2011-01-01

    An algorithm based on compressive sensing (CS) is proposed for synthetic aperture radar (SAR) imaging of moving targets. The received SAR echo is decomposed into the sum of basis sub-signals, which are generated by discretizing the target spatial domain and velocity domain and synthesizing the SAR received data for every discretized spatial position and velocity candidate. In this way, the SAR imaging problem is converted into sub-signal selection problem. In the case that moving targets are sparsely distributed in the observed scene, their reflectivities, positions and velocities can be obtained by using the CS technique. It is shown that, compared with traditional algorithms, the target image obtained by the proposed algorithm has higher resolution and lower side-lobe while the required number of measurements can be an order of magnitude less than that by sampling at Nyquist sampling rate. Moreover, multiple targets with different speeds can be imaged simultaneously, so the proposed algorithm has higher eff...

  10. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng

    2014-03-14

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  11. Satellite SAR and 'in situ' observations of phytoplankton in eutrophic waters

    Science.gov (United States)

    Shomina, Olga; Ermakov, Stanislav; Sergievskaya, Irina; Kapustin, Ivan; da Silva, Jose

    2014-05-01

    The increased eutrophication of shelf areas and inland waters leads to intensive harmful algae bloom and therefore demands new methods of the bloom monitoring. Alpers et al. (2003) from the analysis of satellite optical and radar images of the ocean have concluded that algae bloom can be detected by radar arguing that phytoplankton produces biogenic films which result in the reduced radar backscattering. First direct proof of the relation between radar backscattering, biogenic films and phytoplankton have been obtained by Ermakov et al. (2013), and the physical mechanisms of radar backscatter depression were suggested based on damping of short wind waves due to elastic surface films as well as due to enhanced effective water viscosity. This paper presents results of new experiments on remote sensing of algae bloom. Field observations were carried out on the Gorky Water Reservour from board a ship and from a small motor boat and were co-located and nearly simultaneous with TerraSAR-X image acquisition. Radar backscattering was measured from a ship with an X-band scatterometer, and acoustical scattering due to phytoplankton and the current velocity profiles were recorded with an acoustic Doppler Current Profiler (ADCP) Workhorse Sentinel 600 kHz from the motor boat, moving parallel to the ship track. Water samples and samples of biogenic films were collected from the boat and were analyzed in laboratory. Phytoplankton volume concentration was measured with an optical sensor in YSI 6600 probe, as well as using traditional methods of counting of phytoplankton cells with a Nageotte chamber. Analysis of characteristics of biogenic films sampled with a net method was carried out with a parametric wave method developed at IAP RAS which allowed us to retrieve the film elasticity and the surface tension coefficient. The parametric wave method was also applied to estimate the effective water viscosity in the presence of phytoplankton. Radar backscatter profiles were retrieved

  12. Offshore wind resource mapping for Europe by Synthetic Aperture Radar (SAR) satellite data

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete

    2015-01-01

    For the New European Wind Atlas (NEWA) project with 8 participating countries during5 years (March 2015 – March 2020) we will develop a new wind atlas covering most of the European countries as well as most of the offshore areas in Europe. For the offshore atlas we will rely on a combination...... of satellite remote sensing observations and atmospheric modelling. The satellite data include Synthetic Aperture Radar (SAR) from the European Space Agency from Envisat and the Copernicus mission Sentinel-1. SAR has the advantage of high spatial resolution such that we can cover near-coastal areas where many...... wind farms are planned. In the Danish RUNE project near-shore offshore winds are investigate from SAR, atmospheric modelling and ground-based remote sensing lidar. In the European Space Agency project ResGrow SAR wind resource maps at various locations in the European Seas are used to estimate the wind...

  13. Building detection and building parameter retrieval in InSAR phase images

    Science.gov (United States)

    Dubois, Clémence; Thiele, Antje; Hinz, Stefan

    2016-04-01

    The high resolution provided by the current satellite SAR missions makes them an attractive solution for the detailed analysis of urban areas. Especially due to their weather and daylight independency, they can be employed when optical sensors come to their limits. Due to the specific oblique side-looking configuration of such SAR sensors, phenomena such as layover, double bounce and shadow appear at building location, which can be better understood with very high resolution (VHR) SAR data. The detection of those areas, as well as the retrieval of building parameters through a detailed analysis of the extracted structures, is a challenging task. Indeed, depending on the acquisition configuration, on building material and surroundings, those patterns are not always consistent in amplitude SAR images. They can be difficult to recognize and distinguish automatically. Considering InSAR phase images instead of amplitude images is very helpful for this task, as InSAR is more depending on the geometry. Therefore, in this paper, we focus on the detection and extraction of building layover in InSAR phase images. Two complementing detectors are proposed, and their results are combined, in order to provide reliable building hypotheses. Based on the extracted segments, further analysis is conducted. Especially, the number of connected facades is analyzed. Characteristically geometrical shapes are finally fitted for each facade to permit the determination of the final building parameters as length, width, and height. Results of this approach are shown for three different datasets, first in terms of correctness and completeness of the extraction, and second in terms of accuracy of the extracted building parameters. For the considered datasets, the completeness and correctness are of about 70% and 90%, respectively. Eliminating clear outliers, the determined parameters present an accuracy up to 4 m (length), 2 m (height) and 3 ° (orientation). In this article isolated, middle to

  14. Sparse SAR imaging based on L1/2 regularization

    Institute of Scientific and Technical Information of China (English)

    ZENG JinShan; FANG Jian; XU ZongBen

    2012-01-01

    In this paper,a novel method for synthetic aperture radar (SAR) imaging is proposed.The approach is based on L1/2 regularization to reconstruct the scattering field,which optimizes a quadratic error term of the SAR observation process subject to the interested scene sparsity. Compared to the conventional SAR imaging technique,the new method implements SAR imaging effectively at much lower sampling rate than the Nyquist rate,and produces high-quality images with reduced sidelobes and increased resolution. Also,over the prevalent greedy pursuit and L1 regularization based SAR imaging methods,there are remarkable performance improvements of the new method.On one hand,the new method significantly reduces the number of measurements needed for reconstruction,as supported by a phase transition diagram study.On the other hand,the new method is more robust to the observation noise.These fundamental properties of the new method are supported and demonstrated both by simulations and real SAR data experiments.

  15. Wind class sampling of satellite SAR imagery for offshore wind resource mapping

    DEFF Research Database (Denmark)

    Badger, Merete; Badger, Jake; Nielsen, Morten

    2010-01-01

    High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical-dynamical down......High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical......-dynamical downscaling of large-scale wind conditions using a set of wind classes that describe representative wind situations. One or more SAR scenes are then selected to represent each wind class and the classes are weighted according to their frequency of occurrence. The wind class methodology was originally...... developed for mesoscale modeling of wind resources. Its performance in connection with sampling of SAR scenes is tested against two sets of random SAR samples and meteorological observations at three sites in the North Sea during 2005–08. Predictions of the mean wind speed and the Weibull scale parameter...

  16. Biogeography based Satellite Image Classification

    CERN Document Server

    Panchal, V K; Kaur, Navdeep; Kundra, Harish

    2009-01-01

    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  17. 3-D Target Location from Stereoscopic SAR Images

    Energy Technology Data Exchange (ETDEWEB)

    DOERRY,ARMIN W.

    1999-10-01

    SAR range-Doppler images are inherently 2-dimensional. Targets with a height offset lay over onto offset range and azimuth locations. Just which image locations are laid upon depends on the imaging geometry, including depression angle, squint angle, and target bearing. This is the well known layover phenomenon. Images formed with different aperture geometries will exhibit different layover characteristics. These differences can be exploited to ascertain target height information, in a stereoscopic manner. Depending on the imaging geometries, height accuracy can be on the order of horizontal position accuracies, thereby rivaling the best IFSAR capabilities in fine resolution SAR images. All that is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.

  18. Regional landslide forecasting model using interferometric SAR images

    Institute of Scientific and Technical Information of China (English)

    董育烦; 张发明; 高正夏; 蒯志要

    2008-01-01

    Method of obtaining landslide evaluating information by using Interferometric Synthetic Aperture Radar (InSAR) technique was discussed. More precision landslide surface deformation data extracted from InSAR image need take suitable SAR interferometric data selecting, path tracking, phase unwrapping processes. Then, the DEM model of scope and surface shape of the landslide was built. Combining with geological property of landslide and sliding displacements obtained from InSAR/D-InSAR images, a new landslide forecasting model called equal central angle slice method for those not obviously deformed landslides was put forward. This model breaks the limits of traditional research methods of geology. In this model, the landslide safety factor was calculated by equal central angle slice method, then considering the persistence ratio of the sliding surface based on plastic theory, the minimum safety factor was the phase when plastic area were complete persistence. This new model makes the application of InSAR/D-InSAR technology become more practical in geology hazard research.

  19. Feasibility of sea ice typing with synthetic aperture radar (SAR): Merging of Landsat thematic mapper and ERS 1 SAR satellite imagery

    Science.gov (United States)

    Steffen, Konrad; Heinrichs, John

    1994-01-01

    Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and Landsat thematic mapper (TM) images were acquired for the same area in the Beaufort Sea, April 16 and 18, 1992. The two image pairs were colocated to the same grid (25-m resolution), and a supervised ice type classification was performed on the TM images in order to classify ice free, nilas, gray ice, gray-white ice, thin first-year ice, medium and thick first-year ice, and old ice. Comparison of the collocated SAR pixels showed that ice-free areas can only be classified under calm wind conditions (less than 3 m/s) and for surface winds greater than 10 m/s based on the backscattering coefficient alone. This is true for pack ice regions during the cold months of the year where ice-free areas are spatially limited and where the capillary waves that cause SAR backscatter are dampened by entrained ice crystals. For nilas, two distinct backscatter classes were found at -17 dB and at -10 dB. The higher backscattering coefficient is attributed to the presence of frost flowers on light nilas. Gray and gray-white ice have a backscatter signature similar to first-year ice and therefore cannot be distinguished by SAR alone. First-year and old ice can be clearly separated based on their backscattering coefficient. The performance of the Geophysical Processor System ice classifier was tested against the Landsat derived ice products. It was found that smooth first-year ice and rough first-year ice were not significantly different in the backscatter domain. Ice concentration estimates based on ERS 1 C band SAR showed an error range of 5 to 8% for high ice concentration regions, mainly due to misclassified ice-free and smooth first-year ice areas. This error is expected to increase for areas of lower ice concentration. The combination of C band SAR and TM channels 2, 4, and 6 resulted in ice typing performance with an estimated accuracy of 90% for all seven ice classes.

  20. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2014-01-01

    other documentation. 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC...and Image Processing IX, 2001. [29] J.-F. Aujol, G. Aubert, L. Blanc- Fraud , and A. Chambolle, “Image decomposition application to SAR images,” in

  1. SAR image target segmentation based on entropy maximization and morphology

    Institute of Scientific and Technical Information of China (English)

    柏正尧; 刘洲峰; 何佩琨

    2004-01-01

    Entropy maximization thresholding is a simple, effective image segmentation method. The relation between the histogram entropy and the gray level of an image is analyzed. An approach, which speeds the computation of optimal threshold based on entropy maximization, is proposed. The suggested method has been applied to the synthetic aperture radar (SAR) image targets segmentation. Mathematical morphology works well in reducing the residual noise.

  2. Comparison of Oil Spill Classifications Using Fully and Compact Polarimetric SAR Images

    Directory of Open Access Journals (Sweden)

    Yuanzhi Zhang

    2017-02-01

    Full Text Available In this paper, we present a comparison between several algorithms for oil spill classifications using fully and compact polarimetric SAR images. Oil spill is considered as one of the most significant sources of marine pollution. As a major difficulty of SAR-based oil spill detection algorithms is the classification between mineral and biogenic oil, we focus on quantitatively analyzing and comparing fully and compact polarimetric satellite synthetic aperture radar (SAR modes to detect hydrocarbon slicks over the sea surface, discriminating them from weak-damping surfactants, such as biogenic slicks. The experiment was conducted on quad-pol SAR data acquired during the Norwegian oil-on-water experiment in 2011. A universal procedure was used to extract the features from quad-, dual- and compact polarimetric SAR modes to rank different polarimetric SAR modes and common supervised classifiers. Among all the dual- and compact polarimetric SAR modes, the π/2 mode has the best performance. The best supervised classifiers vary and depended on whether sufficient polarimetric information can be obtained in each polarimetric mode. We also analyzed the influence of the number of polarimetric parameters considered as inputs for the supervised classifiers, onto the detection/discrimination performance. We discovered that a feature set with four features is sufficient for most polarimetric feature-based oil spill classifications. Moreover, dimension reduction algorithms, including principle component analysis (PCA and the local linear embedding (LLE algorithm, were employed to learn low dimensional and distinctive information from quad-polarimetric SAR features. The performance of the new feature sets has comparable performance in oil spill classification.

  3. SAR image formation with azimuth interpolation after azimuth transform

    Science.gov (United States)

    Doerry; Armin W. , Martin; Grant D. , Holzrichter; Michael W.

    2008-07-08

    Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.

  4. Monitoring of wetlands Ecosystems using satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Gruszczynska, M.; Yesou, H.; Hoscilo, A.

    Wetlands are very sensitive ecosystems, functioning as habitat for many organisms. Protection and regeneration of wetlands has been the crucial importance in ecological research and in nature conservation. Knowledge on biophysical properties of wetlands vegetation retrieved from satellite images will enable us to improve monitoring of these unique areas, very often impenetrable. The study covers Biebrza wetland situated in the Northeast part of Poland and is considered as Ramsar Convention test site. The research aims at establishing of changes in biophysical parameters as the scrub encroachment, lowering of the water table, and changes of the farming activity caused ecological changes at these areas. Data from the optical and microwave satellite images collected for the area of Biebrza marshland ecosystem have been analysed and compared with the detailed soil-vegetation ground measurements conducted in conjunction with the overflights. Satellite data include Landsat ETM, ERS-2 ATSR and SAR, SPOT VEGETATION, ENVISAT MERIS and ASAR, and NOAA AVHRR. From the optical data various vegetation indices have been calculated, which characterize the vegetation surface roughness, its moisture conditions and stage of development. Landsat ETM image has been used for classification of wetlands vegetation. For each class of vegetation various moisture indices have been developed. Ground data collected include wet and dry biomass, LAI, vegetation height, and TDR soil moisture. The water cloud model has been applied for retrieval of soil vegetation parameters taking into account microwave satellite images acquired at VV, HV and HH polarisations at different viewing angles. The vegetation parameters have been used for to distinguish changes, which occurred at the area. For each of the vegetation class the soil moisture was calculated from microwave data using developed algorithms. Results of this study will help mapping and monitoring wetlands with the high spatial and temporal

  5. Cauchy pdf modelling and its application to SAR image despeckling

    Institute of Scientific and Technical Information of China (English)

    Chen Guozhong; Liu Xingzhao

    2008-01-01

    Synthetic aperture radar(SAR)imagery is a kind of coherent system that produces a random pattern,named speckle,which degrades the merit of SAR images and affects their further application seriously.Therefore,how to restore SAR image from the speckle has become a necessary step in post-processing of image.A new despeckling method is putforth on the basis of wavelet.First.a new approach on the basis of"second kind statistics"is used to estimate the dispersion parameter of the Cauchy distribution.Then,this Cauchy prior is applied to model the distribution of the wavelet coefficients for the log-transformed reflectance of SAR image.Based on the above ideas,a new homomorphic wavelet-based maximum a posterior(MAP)despeckling method is proposed.Finally,the simulated speckled image and the real SAR image are used to verify our proposed method and the results show that it outperforms the other methods in terms of the speckle reduction and the feature retention.

  6. OIL SPILL DETECTION IN SAR IMAGES USING TEXTURE ENTROPY ALGORITHM AND MAHALANOBIS CLASSIFIER

    Directory of Open Access Journals (Sweden)

    POONAM M BHOGLE

    2012-12-01

    Full Text Available Oil spill has become critical in some countries, especially for countries that have seas or oceans. The situation has caused damage to the environment and polluted the water. To reduce environment damage and protect life in water, plants and soil near to disaster area .Study and analysis should be carried out .The causes and factorsthat lead to the disaster of oil spill should be studied or investigated. To analyze the problem of oil spill we consider 2 algorithms. These methods help in the analysis and identification of oil spill in SAR images. Since the 1980s, satellite-borne synthetic aperture radar (SAR has been investigated for early warning andmonitoring of marine oil spills to permit effective satellite surveillance in the marine environment. Synthetic Aperture Radar (SAR imaging system is used to monitor the marine system. Oil spill pollution plays a significant role in damaging marine ecosystem. One main advantages of SAR is that it can generate imagery under all weather conditions. Automated detection of oil spills from satellite SAR intensity imagery consists of three steps: Detection of dark spots , Extraction of features from the detected dark spots and classification of the dark spots into oil spills and look-alikes.Texture Entropy Algorithm is a method based on the utilization of texture algorithms for the discrimination of oil spill areas from the surrounding features, e.g. sea surface and look-alikes. Mahalanobis Classifier method first estimates covariance matrix and then Mahalanobis Distance is calculated for identification of oil spill or lookalike.

  7. Multi-image Matching of Airborne SAR Imagery by SANCC

    Directory of Open Access Journals (Sweden)

    DING Hao

    2015-03-01

    Full Text Available In order to improve accuracy of SAR matching, a multi-image matching method based on sum of adaptive normalized cross-correlation (SANCC is proposed. It utilizes geometrical and radiometric information of multi-baselinesynthetic aperture radar (SARimages effectively. Firstly, imaging parameters, platform parameters and approximate digital surface model (DSM are used to predict matching line. Secondly, similarity and proximity in Gestalt theory are introduced to SANCC, and SANCC measures of potential matching points along the matching line are calculated. Thirdly, multi-image matching results and object coordinates of matching points are obtained by winner-take-all (WTA optimization strategy. The approach has been demonstrated with airborne SAR images acquired by a Chinese airborne SAR system (CASMSAR system. The experimental results indicate that the proposed algorithm is effective for providing dense and accuracy matching points, reducing the number of mismatches caused by repeated textures, and offering a better solution to match in poor textured areas.

  8. Calibration of a flood inundation model using a SAR image: influence of acquisition time

    Science.gov (United States)

    Van Wesemael, Alexandra; Gobeyn, Sacha; Neal, Jeffrey; Lievens, Hans; Van Eerdenbrugh, Katrien; De Vleeschouwer, Niels; Schumann, Guy; Vernieuwe, Hilde; Di Baldassarre, Giuliano; De Baets, Bernard; Bates, Paul; Verhoest, Niko

    2016-04-01

    Flood risk management has always been in a search for effective prediction approaches. As such, the calibration of flood inundation models is continuously improved. In practice, this calibration process consists of finding the optimal roughness parameters, both channel and floodplain Manning coefficients, since these values considerably influence the flood extent in a catchment. In addition, Synthetic Aperture Radar (SAR) images have been proven to be a very useful tool in calibrating the flood extent. These images can distinguish between wet (flooded) and dry (non-flooded) pixels through the intensity of backscattered radio waves. To this date, however, satellite overpass often occurs only once during a flood event. Therefore, this study is specifically concerned with the effect of the timing of the SAR data acquisition on calibration results. In order to model the flood extent, the raster-based inundation model, LISFLOOD-FP, is used together with a high resolution synthetic aperture radar image (ERS-2 SAR) of a flood event of the river Dee, Wales, in December 2006. As only one satellite image of the considered case study is available, a synthetic framework is implemented in order to generate a time series of SAR observations. These synthetic observations are then used to calibrate the model at different time instants. In doing so, the sensitivity of the model output to the channel and floodplain Manning coefficients is studied through time. As results are examined, these suggest that there is a clear difference in the spatial variability to which water is held within the floodplain. Furthermore, these differences seem to be variable through time. Calibration by means of satellite flood observations obtained from the rising or receding limb, would generally lead to more reliable results rather than near peak flow observations.

  9. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2013-01-01

    This new process is also valuable for many SAR image understanding tasks such as road detection, railway detection, ship wake detection, texture...Starck, and L. Boubchir, “Morphological diversity and sparse image denoising,” in Proc. IEEE Int. Conf. Acoust . Speech Signal Process., vol. 1. Apr

  10. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross section...

  11. Satellite SAR applied in offhore wind resource mapping: possibilities and limitations

    Science.gov (United States)

    Hasager, C. B.

    Satellite remote sensing of ocean wind fields from Synthetic Aperture Radar (SAR) observations is presented. The study is based on a series of more than 60 ERS-2 SAR satellite scenes from the Horns Rev in the North Sea. The wind climate from the coastline and 80 km offshore is mapped in detail with a resolution of 400 m by 400 m grid cells. Spatial variations in wind speed as a function of wind direction and fetch are observed and discussed. The satellite wind fields are compared to in-situ observations from a tall offshore meteorological mast at which wind speed at 4 levels are analysed. The mast is located 14 km offshore and the wind climate is observed continously since May 1999. For offshore wind resource mapping the SAR-based wind field maps can constitute an alternative to in-situ observations and a practical method is developed for applied use in WAsP (Wind Atlas Analysis and Application Program). The software is the de facto world standard tool used for prediction of wind climate and power production from wind turbines and wind farms. The possibilities and limitations on achieving offshore wind resource estimates using SAR-based wind fields in lieu of in-situ data are discussed. It includes a presentation of the footprint area-averaging techniques tailored for SAR-based wind field maps. Averaging techniques are relevant for the reduction of noise apparent in SAR wind speed maps. Acknowledgments: Danish Research Agency (SAT-WIND Sagsnr. 2058-03-0006) for funding, ESA (EO-1356, AO-153) for ERS-2 SAR scenes, and Elsam Engineering A/S for in-situ met-data.

  12. Classification of Polarimetric SAR Image Based on the Subspace Method

    Science.gov (United States)

    Xu, J.; Li, Z.; Tian, B.; Chen, Q.; Zhang, P.

    2013-07-01

    Land cover classification is one of the most significant applications in remote sensing. Compared to optical sensing technologies, synthetic aperture radar (SAR) can penetrate through clouds and have all-weather capabilities. Therefore, land cover classification for SAR image is important in remote sensing. The subspace method is a novel method for the SAR data, which reduces data dimensionality by incorporating feature extraction into the classification process. This paper uses the averaged learning subspace method (ALSM) method that can be applied to the fully polarimetric SAR image for classification. The ALSM algorithm integrates three-component decomposition, eigenvalue/eigenvector decomposition and textural features derived from the gray-level cooccurrence matrix (GLCM). The study site, locates in the Dingxing county, in Hebei Province, China. We compare the subspace method with the traditional supervised Wishart classification. By conducting experiments on the fully polarimetric Radarsat-2 image, we conclude the proposed method yield higher classification accuracy. Therefore, the ALSM classification method is a feasible and alternative method for SAR image.

  13. G0-WISHART DISTRIBUTION BASED CLASSIFICATION FROM POLARIMETRIC SAR IMAGES

    Directory of Open Access Journals (Sweden)

    G. C. Hu

    2017-09-01

    Full Text Available Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

  14. G0-WISHART Distribution Based Classification from Polarimetric SAR Images

    Science.gov (United States)

    Hu, G. C.; Zhao, Q. H.

    2017-09-01

    Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

  15. Bistatic SAR: Proof of Concept.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Doren, Neall E.; Bacon, Terry A.; Wahl, Daniel E.; Eichel, Paul H.; Jakowatz, Charles V,; Delaplain, Gilbert G.; Dubbert, Dale F.; Tise, Bertice L.; White, Kyle R.

    2014-10-01

    Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

  16. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

  17. Shadow imaging of geosynchronous satellites

    Science.gov (United States)

    Douglas, Dennis Michael

    Geosynchronous (GEO) satellites are essential for modern communication networks. If communication to a GEO satellite is lost and a malfunction occurs upon orbit insertion such as a solar panel not deploying there is no direct way to observe it from Earth. Due to the GEO orbit distance of ~36,000 km from Earth's surface, the Rayleigh criteria dictates that a 14 m telescope is required to conventionally image a satellite with spatial resolution down to 1 m using visible light. Furthermore, a telescope larger than 30 m is required under ideal conditions to obtain spatial resolution down to 0.4 m. This dissertation evaluates a method for obtaining high spatial resolution images of GEO satellites from an Earth based system by measuring the irradiance distribution on the ground resulting from the occultation of the satellite passing in front of a star. The representative size of a GEO satellite combined with the orbital distance results in the ground shadow being consistent with a Fresnel diffraction pattern when observed at visible wavelengths. A measurement of the ground shadow irradiance is used as an amplitude constraint in a Gerchberg-Saxton phase retrieval algorithm that produces a reconstruction of the satellite's 2D transmission function which is analogous to a reverse contrast image of the satellite. The advantage of shadow imaging is that a terrestrial based redundant set of linearly distributed inexpensive small telescopes, each coupled to high speed detectors, is a more effective resolved imaging system for GEO satellites than a very large telescope under ideal conditions. Modeling and simulation efforts indicate sub-meter spatial resolution can be readily achieved using collection apertures of less than 1 meter in diameter. A mathematical basis is established for the treatment of the physical phenomena involved in the shadow imaging process. This includes the source star brightness and angular extent, and the diffraction of starlight from the satellite

  18. Ensemble polarimetric SAR image classification based on contextual sparse representation

    Science.gov (United States)

    Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun

    2016-05-01

    Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.

  19. Modelling Iteration Convergence Condition for Single SAR Image Geocoding

    Science.gov (United States)

    Dong, Yuting; Liao, Minghsheng; Zhang, Lu; Shi, Xuguo

    2014-11-01

    Single SAR image geocoding is to determine the ground coordinate for each pixel in the SAR image assisted with an external DEM. Due to the uncertainty of the elevation of each pixel in SAR image, an iterative procedure is needed, which suffers from the problem of divergence in some difficult areas such as shaded and serious layover areas. This paper aims at theoretically analysing the convergence conditions that has not been intensively studied till now. To make the discussion easier, the Range-Doppler (RD) model is simplified and then the general surface is simplified into a planar surface. Mathematical deduction is carried out to derive the convergence conditions and the impact factors for the convergence speed are analysed. The theoretical findings are validated by experiments for both simulated and real surfaces.

  20. Compressive SAR imaging with joint sparsity and local similarity exploitation.

    Science.gov (United States)

    Shen, Fangfang; Zhao, Guanghui; Shi, Guangming; Dong, Weisheng; Wang, Chenglong; Niu, Yi

    2015-02-12

    Compressive sensing-based synthetic aperture radar (SAR) imaging has shown its superior capability in high-resolution image formation. However, most of those works focus on the scenes that can be sparsely represented in fixed spaces. When dealing with complicated scenes, these fixed spaces lack adaptivity in characterizing varied image contents. To solve this problem, a new compressive sensing-based radar imaging approach with adaptive sparse representation is proposed. Specifically, an autoregressive model is introduced to adaptively exploit the structural sparsity of an image. In addition, similarity among pixels is integrated into the autoregressive model to further promote the capability and thus an adaptive sparse representation facilitated by a weighted autoregressive model is derived. Since the weighted autoregressive model is inherently determined by the unknown image, we propose a joint optimization scheme by iterative SAR imaging and updating of the weighted autoregressive model to solve this problem. Eventually, experimental results demonstrated the validity and generality of the proposed approach.

  1. Effect of beam-pointing errors on bistatic SAR imaging

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The purpose is to conduct a research in the energy variation of echo wave and the imaging effect caused by the aero bistatic SAR pointing errors.Based on the moving geometry configuration of aero bistatic SAR,a model of beam pointing errors is built.Based on this,the azimuth Doppler frequency center estimation caused by these errors and the limitation to the beam pointing synchronization error are studied,and then the imaging result of different errors are analyzed.The computer's simulations are provided to prove the validity of the above analysis.

  2. An automatic coastline detector for use with SAR images

    Energy Technology Data Exchange (ETDEWEB)

    Erteza, Ireena A.

    1998-09-01

    SAR imagery for coastline detection has many potential advantages over conventional optical stereoscopic techniques. For example, SAR does not have restrictions on being collected during daylight or when there is no cloud cover. In addition, the techniques for coastline detection witth SAR images can be automated. In this paper, we present the algorithmic development of an automatic coastline detector for use with SAR imagery. Three main algorithms comprise the automatic coastline detection algorithm, The first algorithm considers the image pre-processing steps that must occur on the original image in order to accentuate the land/water boundary. The second algorithm automatically follows along the accentuated land/water boundary and produces a single-pixel-wide coastline. The third algorithm identifies islands and marks them. This report describes in detail the development of these three algorithms. Examples of imagery are used throughout the paper to illustrate the various steps in algorithms. Actual code is included in appendices. The algorithms presented are preliminary versions that can be applied to automatic coastline detection in SAR imagery. There are many variations and additions to the algorithms that can be made to improve robustness and automation, as required by a particular application.

  3. Spacial Variation in SAR Images of Different Resolution for Agricultural Fields

    DEFF Research Database (Denmark)

    Sandholt, Inge; Skriver, Henning

    1999-01-01

    The spatial variation in two types of Synthetic Aperture Radar (SAR) images covering agricultural fields is analysed. C-band polarimetric SAR data from the Danish airborne SAR, EMISAR, have been compared to space based ERS-1 C-band SAR with respect to scale and effect of polarization. The general...

  4. Polar format algorithm for SAR imaging with Matlab

    Science.gov (United States)

    Deming, Ross; Best, Matthew; Farrell, Sean

    2014-06-01

    Due to its computational efficiency, the polar format algorithm (PFA) is considered by many to be the workhorse for airborne synthetic aperture radar (SAR) imaging. PFA is implemented in spatial Fourier space, also known as "K-space", which is a convenient domain for understanding SAR performance metrics, sampling requirements, etc. In this paper the mathematics behind PFA are explained and computed examples are presented, both using simulated data, and experimental airborne radar data from the Air Force Research Laboratory (AFRL) Gotcha Challenge collect. In addition, a simple graphical method is described that can be used to model and predict wavefront curvature artifacts in PFA imagery, which are due to the limited validity of the underlying far-field approximation. The appendix includes Matlab code for computing SAR images using PFA.

  5. Geodetic imaging of tectonic deformation with InSAR

    Science.gov (United States)

    Fattahi, Heresh

    Precise measurements of ground deformation across the plate boundaries are crucial observations to evaluate the location of strain localization and to understand the pattern of strain accumulation at depth. Such information can be used to evaluate the possible location and magnitude of future earthquakes. Interferometric Synthetic Aperture Radar (InSAR) potentially can deliver small-scale (few mm/yr) ground displacement over long distances (hundreds of kilometers) across the plate boundaries and over continents. However, Given the ground displacement as our signal of interest, the InSAR observations of ground deformation are usually affected by several sources of systematic and random noises. In this dissertation I identify several sources of systematic and random noise, develop new methods to model and mitigate the systematic noise and to evaluate the uncertainty of the ground displacement measured with InSAR. I use the developed approach to characterize the tectonic deformation and evaluate the rate of strain accumulation along the Chaman fault system, the western boundary of the India with Eurasia tectonic plates. I evaluate the bias due to the topographic residuals in the InSAR range-change time-series and develope a new method to estimate the topographic residuals and mitigate the effect from the InSAR range-change time-series (Chapter 2). I develop a new method to evaluate the uncertainty of the InSAR velocity field due to the uncertainty of the satellite orbits (Chapter 3) and a new algorithm to automatically detect and correct the phase unwrapping errors in a dense network of interferograms (Chapter 4). I develop a new approach to evaluate the impact of systematic and stochastic components of the tropospheric delay on the InSAR displacement time-series and its uncertainty (Chapter 5). Using the new InSAR time-series approach developed in the previous chapters, I study the tectonic deformation across the western boundary of the India plate with Eurasia and

  6. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  7. System Design of a S-band Solid-state Transmitter in Satellite-borne SAR

    Directory of Open Access Journals (Sweden)

    Zhao Hai-yang

    2014-06-01

    Full Text Available The system design of a S-band solid-state transmitter in satellite-borne SAR is introduced. A series of critical technologies, such as high reliability, environmental adaptability, and structure miniaturization, which are necessary in satellite applications, are analyzed and discussed. The technologies are experimentally verified at different periods. Multichannel combined technology is used for the transmitter, and the output peak power is more than 3 kW. Because of the high efficiency, small size, lightweight, and high power, it is especially applicable in small satellite platforms.

  8. THE SIMULATION OF THE SAR IMAGE OF INTERNAL SOLITARY WAVES IN ALBORAN SEA

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    SAR imaging mechanism of internal wave is studied. The numerical modelling of internal waves is obtained by the two-level scheme. The simulaed SAR images that have better expressed the features of internal waves are given by the internal waves SAR imaging theory and numerical modelling result.

  9. Monitoring water level using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) images

    Science.gov (United States)

    Stavroulaki, Eleni; Alexakis, Dimitrios D.; Tsanis, Ioannis K.

    2017-04-01

    Interferometric Synthetic Aperture Radar (SAR) methodology can successfully detect phase variations related to water level changes and produce corresponding water level maps. Two lakes located in Western Crete, Greece, namely Lake Kournas and Lake Agia were used as case studies to study water level change with means of SAR interferometry. The change of the water surface in the lake is examined over a period of two years, 2015-2016 using Sentinel 1 IW mode images and in situ water level data. Initially, all the SAR images were preprocessed in terms of atmospheric and radiometric corrections. Various interferograms were developed to study the multi-temporal regime of water level in both lakes. Optical satellite sensor data (Landsat 8) were used to study the vegetation regime and how this affect the interferogram processing. The results denoted the fact that the combination of SAR backscattering intensity and unwrapped phase water level data can provide additional insight into hydrological state. It is also shown that integrated analysis of the backscattering mechanism and interferometric characteristics can considerably enhance the reliability of the water-level retrieval scheme and optimize the capture of hydrological patterns spatial distribution. Keywords: Sentinel-1, interferogram, water level, Backscattering

  10. Improved Early Crop Type Identification By Joint Use of High Temporal Resolution SAR And Optical Image Time Series

    Directory of Open Access Journals (Sweden)

    Jordi Inglada

    2016-04-01

    Full Text Available High temporal and spatial resolution optical image time series have been proven efficient for crop type mapping at the end of the agricultural season. However, due to cloud cover and image availability, crop identification earlier in the season is difficult. The recent availability of high temporal and spatial resolution SAR image time series, opens the possibility of improving early crop type mapping. This paper studies the impact of such SAR image time series when used in complement of optical imagery. The pertinent SAR image features, the optimal working resolution, the effect of speckle filtering and the use of temporal gap-filling of the optical image time series are assessed. SAR image time series as those provided by the Sentinel-1 satellites allow significant improvements in terms of land cover classification, both in terms of accuracy at the end of the season and for early crop identification. Haralik textures (Entropy, Inertia, the polarization ratio and the local mean together with the VV imagery were found to be the most pertinent features. Working at at 10 m resolution and using speckle filtering yield better results than other configurations. Finally it was shown that the use of SAR imagery allows to use optical data without gap-filling yielding results which are equivalent to the use of gap-filling in the case of perfect cloud screening, and better results in the case of cloud screening errors.

  11. Multi-Mode GF-3 Satellite Image Geometric Accuracy Verification Using the RPC Model.

    Science.gov (United States)

    Wang, Taoyang; Zhang, Guo; Yu, Lei; Zhao, Ruishan; Deng, Mingjun; Xu, Kai

    2017-09-01

    The GaoFen-3 (GF-3) satellite is the first C-band multi-polarization synthetic aperture radar (SAR) imaging satellite with a resolution up to 1 m in China. It is also the only SAR satellite of the High-Resolution Earth Observation System designed for civilian use. There are 12 different imaging models to meet the needs of different industry users. However, to use SAR satellite images for related applications, they must possess high geometric accuracy. In order to verify the geometric accuracy achieved by the different modes of GF-3 images, we analyze the SAR geometric error source and perform geometric correction tests based on the RPC model with and without ground control points (GCPs) for five imaging modes. These include the spotlight (SL), ultra-fine strip (UFS), Fine Strip I (FSI), Full polarized Strip I (QPSI), and standard strip (SS) modes. Experimental results show that the check point residuals are large and consistent without GCPs, but the root mean square error of the independent checkpoints for the case of four corner control points is better than 1.5 pixels, achieving a similar level of geometric positioning accuracy to that of international satellites. We conclude that the GF-3 satellite can be used for high-accuracy geometric processing and related industry applications.

  12. Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms

    Directory of Open Access Journals (Sweden)

    Konstantinos N. Topouzelis

    2008-10-01

    Full Text Available This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject.

  13. Texture analysis and classification of SAR images of urban areas

    NARCIS (Netherlands)

    Dekker, R.J.

    2003-01-01

    In SAR image classification texture holds useful information. In a study after the ability of texture to discriminate urban land-cover, a set of measures was investigated. Among them were histogram measures, wavelet energy, fractal dimension, lacunarity and semivariograms. The latter were chosen as

  14. Unsupervised Classification of SAR Images using Hierarchical Agglomeration and EM

    NARCIS (Netherlands)

    Kayabol, K.; Krylov, V.; Zerubia, J.; Salerno, E.; Cetin, A.E.; Salvetti, O.

    2012-01-01

    We implement an unsupervised classification algorithm for high resolution Synthetic Aperture Radar (SAR) images. The foundation of algorithm is based on Classification Expectation-Maximization (CEM). To get rid of two drawbacks of EM type algorithms, namely the initialization and the model order sel

  15. SAR image autofocus by sharpness optimization: a theoretical study.

    Science.gov (United States)

    Morrison, Robert L; Do, Minh N; Munson, David C

    2007-09-01

    Synthetic aperture radar (SAR) autofocus techniques that optimize sharpness metrics can produce excellent restorations in comparison with conventional autofocus approaches. To help formalize the understanding of metric-based SAR autofocus methods, and to gain more insight into their performance, we present a theoretical analysis of these techniques using simple image models. Specifically, we consider the intensity-squared metric, and a dominant point-targets image model, and derive expressions for the resulting objective function. We examine the conditions under which the perfectly focused image models correspond to stationary points of the objective function. A key contribution is that we demonstrate formally, for the specific case of intensity-squared minimization autofocus, the mechanism by which metric-based methods utilize the multichannel defocusing model of SAR autofocus to enforce the stationary point property for multiple image columns. Furthermore, our analysis shows that the objective function has a special separble property through which it can be well approximated locally by a sum of 1-D functions of each phase error component. This allows fast performance through solving a sequence of 1-D optimization problems for each phase component simultaneously. Simulation results using the proposed models and actual SAR imagery confirm that the analysis extends well to realistic situations.

  16. UWB front-end for SAR-based imaging system

    NARCIS (Netherlands)

    Monni, S.; Grooters, R.; Neto, A.; Nennie, F.A.

    2010-01-01

    A planarly fed UWB leaky lens antenna is presented integrated with wide band transmit and receive front-end electronics, to be used in a SAR-based imaging system. The unique non-dispersive characteristics of this antenna over a very wide bandwidth, together with the dual band front-end electronics b

  17. Satellite SAR interferometric observations of displacements associated with urban subsidence in Suzhou, Eastern China

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    SAR interferometry (InSAR) has a high potential for surface displacement mapping in the range from millimeter to meter. In this paper the potential of ERS-1/2 SAR interferometry for mapping subtle land subsidence has been investigated. A time series of ERS-1/2 SAR data from February 1993 to February 2000 is collected from measurements taken in Suzhou city, Jiangsu Province, China, eight ERS-1/2 SAR images are used to create seven interferograms, and three differential interferograms are produced using the three-pass method, which clearly show the spatial extent of land subsidence. The deformation maps are validated by leveling surveys, the correlation coefficient and standard deviation between them are 0.943 and 0.1706 respectively. Based on seven benchmarks, the subsidence rates are estimated, the overall trends are in close agreement with InSAR results. The results of study show that for the mapping of land subsidence in urban environments InSAR has a strong potential due to its cost-saving, high resolution and accuracy.

  18. Smoothing of Fused Spectral Consistent Satellite Images

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2006-01-01

    on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. (2005) proposed a method of fusion of satellite images that is based on the properties of imaging physics...

  19. THz-SAR Vibrating Target Imaging via the Bayesian Method

    Directory of Open Access Journals (Sweden)

    Bin Deng

    2017-01-01

    Full Text Available Target vibration bears important information for target recognition, and terahertz, due to significant micro-Doppler effects, has strong advantages for remotely sensing vibrations. In this paper, the imaging characteristics of vibrating targets with THz-SAR are at first analyzed. An improved algorithm based on an excellent Bayesian approach, that is, the expansion-compression variance-component (ExCoV method, has been proposed for reconstructing scattering coefficients of vibrating targets, which provides more robust and efficient initialization and overcomes the deficiencies of sidelobes as well as artifacts arising from the traditional correlation method. A real vibration measurement experiment of idle cars was performed to validate the range model. Simulated SAR data of vibrating targets and a tank model in a real background in 220 GHz show good performance at low SNR. Rapidly evolving high-power terahertz devices will offer viable THz-SAR application at a distance of several kilometers.

  20. An Improved Shape Contexts Based Ship Classification in SAR Images

    Directory of Open Access Journals (Sweden)

    Ji-Wei Zhu

    2017-02-01

    Full Text Available In synthetic aperture radar (SAR imagery, relating to maritime surveillance studies, the ship has always been the main focus of study. In this letter, a method of ship classification in SAR images is proposed to enhance classification accuracy. In the proposed method, to fully exploit the distinguishing characters of the ship targets, both topology and intensity of the scattering points of the ship are considered. The results of testing the proposed method on a data set of three types of ships, collected via a space-borne SAR sensor designed by the Institute of Electronics, Chinese Academy of Sciences (IECAS, establish that the proposed method is superior to several existing methods, including the original shape contexts method, traditional invariant moments and the recent approach.

  1. Comparison of Orbit-Based and Time-Offset-Based Geometric Correction Models for SAR Satellite Imagery Based on Error Simulation.

    Science.gov (United States)

    Hong, Seunghwan; Choi, Yoonjo; Park, Ilsuk; Sohn, Hong-Gyoo

    2017-01-17

    Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various geometric correction models have been developed and applied. However, it is still difficult for general users to adopt a suitable geometric correction models having sufficient precision. In this regard, this paper evaluated the orbit-based and time-offset-based models with an error simulation. To evaluate the geometric correction models, Radarsat-1 images that have large errors in satellite orbit information and TerraSAR-X images that have a reportedly high accuracy in satellite orbit and sensor information were utilized. For Radarsat-1 imagery, the geometric correction model based on the satellite position parameters has a better performance than the model based on time-offset parameters. In the case of the TerraSAR-X imagery, two geometric correction models had similar performance and could ensure sub-pixel geolocation accuracy.

  2. Comparison of Orbit-Based and Time-Offset-Based Geometric Correction Models for SAR Satellite Imagery Based on Error Simulation

    Science.gov (United States)

    Hong, Seunghwan; Choi, Yoonjo; Park, Ilsuk; Sohn, Hong-Gyoo

    2017-01-01

    Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various geometric correction models have been developed and applied. However, it is still difficult for general users to adopt a suitable geometric correction models having sufficient precision. In this regard, this paper evaluated the orbit-based and time-offset-based models with an error simulation. To evaluate the geometric correction models, Radarsat-1 images that have large errors in satellite orbit information and TerraSAR-X images that have a reportedly high accuracy in satellite orbit and sensor information were utilized. For Radarsat-1 imagery, the geometric correction model based on the satellite position parameters has a better performance than the model based on time-offset parameters. In the case of the TerraSAR-X imagery, two geometric correction models had similar performance and could ensure sub-pixel geolocation accuracy. PMID:28106729

  3. Comparison of Orbit-Based and Time-Offset-Based Geometric Correction Models for SAR Satellite Imagery Based on Error Simulation

    Directory of Open Access Journals (Sweden)

    Seunghwan Hong

    2017-01-01

    Full Text Available Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various geometric correction models have been developed and applied. However, it is still difficult for general users to adopt a suitable geometric correction models having sufficient precision. In this regard, this paper evaluated the orbit-based and time-offset-based models with an error simulation. To evaluate the geometric correction models, Radarsat-1 images that have large errors in satellite orbit information and TerraSAR-X images that have a reportedly high accuracy in satellite orbit and sensor information were utilized. For Radarsat-1 imagery, the geometric correction model based on the satellite position parameters has a better performance than the model based on time-offset parameters. In the case of the TerraSAR-X imagery, two geometric correction models had similar performance and could ensure sub-pixel geolocation accuracy.

  4. Chest X-ray imaging of patients with SARS

    Institute of Scientific and Technical Information of China (English)

    陆普选; 周伯平; 陈心春; 袁明远; 龚小龙; 杨根东; 刘锦清; 袁本通; 郑广平; 杨桂林; 王火生

    2003-01-01

    Objective To investigate the chest X-ray manifestations of SARS cases.Methods A retrospective study was conducted among 52 clinically confirmed SARS patients from February 9 to May 10, 2003. Chest X-ray scanning was performed at a interval of 1-3 days according to the requirements. The manifestations and special features of SARS in X-ray were analyzed. Results Small or large patchy shadows with intensive density in both lungs were observed in 31 cases, ground-glass like opacification in 16, small patchy shadows in one lung lobe or one lung segment in 18, nodular shadows in one lung segment in 1, and increased lung marking in lung interstitial tissues in 2. Rapidly changing consolidations revealed in chest X-ray images were found to be associated with SARS infections, and they were not affected by treatment with antibiotics.Conclusion Chest X-ray provides a sensitive and specific method for the diagnosis and treatment of SARS, and those present with symptoms and signs should undergo chest X-ray scanning every 1-3 days.

  5. Feature preserving compression of high resolution SAR images

    Science.gov (United States)

    Yang, Zhigao; Hu, Fuxiang; Sun, Tao; Qin, Qianqing

    2006-10-01

    Compression techniques are required to transmit the large amounts of high-resolution synthetic aperture radar (SAR) image data over the available channels. Common Image compression methods may lose detail and weak information in original images, especially at smoothness areas and edges with low contrast. This is known as "smoothing effect". It becomes difficult to extract and recognize some useful image features such as points and lines. We propose a new SAR image compression algorithm that can reduce the "smoothing effect" based on adaptive wavelet packet transform and feature-preserving rate allocation. For the reason that images should be modeled as non-stationary information resources, a SAR image is partitioned to overlapped blocks. Each overlapped block is then transformed by adaptive wavelet packet according to statistical features of different blocks. In quantifying and entropy coding of wavelet coefficients, we integrate feature-preserving technique. Experiments show that quality of our algorithm up to 16:1 compression ratio is improved significantly, and more weak information is reserved.

  6. A General Epipolar-Line Model between Optical and SAR Images and Used in Image Matching

    Directory of Open Access Journals (Sweden)

    Shuai Xing

    2014-02-01

    Full Text Available The search space and strategy are important for optical and SAR image matching. In this paper a general epipolar-line model has been proposed between linear array push-broom optical and SAR images. Then a dynamic approximate epipolar-line constraint model (DAELCM has been constructed and used to construct a new image matching algorithm with Harris operator and CRA. Experimental results have shown that the general epipolar-line model is valid and successfully used in optical and SAR image matching, and effectively limits the search space and decreased computation.

  7. Restoration of polarimetric SAR images using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning

    2001-01-01

    approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented...... are obtained while at the same time preserving most of the structures in the image. The algorithm is evaluated using multilook polarimetric L-band data from the Danish airborne EMISAR system, and the impact of the algorithm on the unsupervised H-α classification is demonstrated......Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering...

  8. SAR IMAGE ENHANCEMENT BASED ON BEAM SHARPENING TECHNIQUE

    Institute of Scientific and Technical Information of China (English)

    LIYong; ZI-IANGKun-hui; ZHUDai-yin; ZHUZhao-da

    2004-01-01

    A major problem encountered in enhancing SAR image is the total loss of phase information and the unknown parameters of imaging system. The beam sharpening technique, combined with synthetic aperture radiation pattern estimation provides an approach to process this kind of data to achieve higher apparent resolution. Based on the criterion of minimizing the expected quadratic estimation error, an optimum FIR filter with a symmetrical structure is designed whose coefficients depend on the azimuth response of local isolated prominent points because this response can be approximately regarded as the synthetic aperture radiation pattern of the imaging system. The point target simulation shows that the angular resolution is improved by a ratio of almost two to one. The processing results of a live SAR image demonstrate the validity of the method.

  9. Image Combination Analysis in SPECAN Algorithm of Spaceborne SAR

    Institute of Scientific and Technical Information of China (English)

    臧铁飞; 李方慧; 龙腾

    2003-01-01

    An analysis of image combination in SPECAN algorithm is delivered in time-frequency domain in detail and a new image combination method is proposed. For four multi-looks processing one sub-aperture data in every three sub-apertures is processed in this combination method. The continual sub-aperture processing in SPECAN algorithm is realized and the processing efficiency can be dramatically increased. A new parameter is also put forward to measure the processing efficient of SAR image processing. Finally, the raw data of RADARSAT are used to test the method and the result proves that this method is feasible to be used in SPECAN algorithm of spaceborne SAR and can improve processing efficiently. SPECAN algorithm with this method can be used in quick-look imaging.

  10. Multiscale Segmentation of Polarimetric SAR Image Based on Srm Superpixels

    Science.gov (United States)

    Lang, F.; Yang, J.; Wu, L.; Li, D.

    2016-06-01

    Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.

  11. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  12. a SAR Image Registration Method Based on Sift Algorithm

    Science.gov (United States)

    Lu, W.; Yue, X.; Zhao, Y.; Han, C.

    2017-09-01

    In order to improve the stability and rapidity of synthetic aperture radar (SAR) images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  13. A Level Set Filter for Speckle Reduction in SAR Images

    OpenAIRE

    Huang Bo; Li Hongga; Huang Xiaoxia

    2010-01-01

    Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can b...

  14. Monitoring small reservoirs in semi-arid region by satellite SAR data

    Science.gov (United States)

    Nicolina Papa, Maria; Mitidieri, Francesco; Amitrano, Donato; Ruello, Giuseppe; Di Martino, Gerardo; Iodice, Antonio; Riccio, Daniele

    2016-04-01

    The work presents a novel tool for the monitoring of small reservoirs in semi-arid regions. The pilot project was developed in the Yatenga region, a Sahelian area in northern Burkina Faso. In semi-arid regions, small reservoirs are widely employed for facing seasonal variability in water availability due to the alternation of a rainy (3 months) and a dry (9 months) season. Beside their crucial importance, the small reservoirs are not appropriately monitored, they are often built for the initiative of small local communities and even basic data as their location and capacity are not available. Another major problem is linked to soil erosion due to water and consequent reservoirs' sedimentation that reduces the amount of available water and the life span of reservoirs. This lack of data prevents the implementation of strategies for the optimization of water resources management. It is therefore necessary to improve the data availability through the development of cost-effective monitoring techniques and to adapt the hydrological modeling to the limited available data. In this context the use if satellite data can highly contribute to the achievement of crucial information at low costs, high resolution in time and wide areas. In the present work, we used COSMO-SkyMed Stripmap (3m resolution) and Spotligth (1m resolution) Synthetic Aperture Radar (SAR) data acquired under the aegis of the 2007 Italian Space Agency Announcement of Opportunity and of the HydroCIDOT project. The shorelines of the reservoirs were extracted from the series of SAR images by employing an innovative change-detection framework. A digital elevation model (DEM) of the study area was obtained via standard interferometry processing of images acquired at the end of the dry season, when small reservoirs are completely empty, and information about the surface usually covered by water can be retrieved. The obtained DEM and shorelines were used for bathymetry extraction of reservoirs. For the

  15. Fine-scale features on the sea surface in SAR satellite imagery – Part 1: Simultaneous in-situ measurements

    Directory of Open Access Journals (Sweden)

    S. Brusch

    2012-09-01

    Full Text Available This work is aimed at identifying the origin of fine-scale features on the sea surface in synthetic aperture radar (SAR imagery with the help of in-situ measurements as well as numerical models (presented in a companion paper. We are interested in natural and artificial features starting from the horizontal scale of the upper ocean mixed layer, around 30–50 m. These features are often associated with three-dimensional upper ocean dynamics. We have conducted a number of studies involving in-situ observations in the Straits of Florida during SAR satellite overpass. The data include examples of sharp frontal interfaces, wakes of surface ships, internal wave signatures, as well as slicks of artificial and natural origin. Atmospheric processes, such as squall lines and rain cells, produced prominent signatures on the sea surface. This data has allowed us to test an approach for distinguishing between natural and artificial features and atmospheric influences in SAR images that is based on a co-polarized phase difference filter.

  16. PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform

    Institute of Scientific and Technical Information of China (English)

    LIU Meijie; DAI Yongshou; ZHANG Jie; ZHANG Xi; MENG Junmin; XIE Qinchuan

    2015-01-01

    Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral in-formation, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be im-proved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transfor-mation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar (ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensi-ty-saturation (HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue (RGB) space, and the optical image from the China-Brazil Earth Resources Satellite (CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis (PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea

  17. A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions

    Science.gov (United States)

    Huang, Shiqi; Huang, Wenzhun; Zhang, Ting

    2016-12-01

    The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application.

  18. A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR.

    Science.gov (United States)

    Zeng, Hong-Cheng; Wang, Peng-Bo; Chen, Jie; Liu, Wei; Ge, LinLin; Yang, Wei

    2016-02-26

    Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) recently plays a more and more significant role in remote sensing applications for its low-cost and real-time global coverage capability. In this paper, a general imaging formation algorithm was proposed for accurately and efficiently focusing GNSS-based bistatic SAR data, which avoids the interpolation processing in traditional back projection algorithms (BPAs). A two-dimensional point target spectrum model was firstly presented, and the bulk range cell migration correction (RCMC) was consequently derived for reducing range cell migration (RCM) and coarse focusing. As the bulk RCMC seriously changes the range history of the radar signal, a modified and much more efficient hybrid correlation operation was introduced for compensating residual phase errors. Simulation results were presented based on a general geometric topology with non-parallel trajectories and unequal velocities for both transmitter and receiver platforms, showing a satisfactory performance by the proposed method.

  19. A Compressive Sensing SAR Imaging Approach Based on Wavelet Package Algorithm

    Directory of Open Access Journals (Sweden)

    Shi Yan

    2013-06-01

    Full Text Available Compressive sensing SAR imaging can significantly reduce the sampling rate and the amount of data,but it is essential only in the case where the reflection coefficients of SAR scene are sparse. This paper proposed a compressive sensing SAR imaging method based on wavelet packet sparse representation. The wavelet packet algorithm is used to choose the most sparse representation of the SAR scene by training the same type of SAR images. By solving for the minimum 1 l norm optimization, the SAR scene reflection coefficients can be reconstructed. Unambiguous SAR image can be produced with the proposed method even with fewer samples. SAR data simulation experiments demonstrate the efficiency of the proposed method.

  20. SAR Image Segmentation Based On Hybrid PSOGSA Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Amandeep Kaur

    2014-09-01

    Full Text Available Image segmentation is useful in many applications. It can identify the regions of interest in a scene or annotate the data. It categorizes the existing segmentation algorithm into region-based segmentation, data clustering, and edge-base segmentation. Region-based segmentation includes the seeded and unseeded region growing algorithms, the JSEG, and the fast scanning algorithm. Due to the presence of speckle noise, segmentation of Synthetic Aperture Radar (SAR images is still a challenging problem. We proposed a fast SAR image segmentation method based on Particle Swarm Optimization-Gravitational Search Algorithm (PSO-GSA. In this method, threshold estimation is regarded as a search procedure that examinations for an appropriate value in a continuous grayscale interval. Hence, PSO-GSA algorithm is familiarized to search for the optimal threshold. Experimental results indicate that our method is superior to GA based, AFS based and ABC based methods in terms of segmentation accuracy, segmentation time, and Thresholding.

  1. Dynamic and data-driven classification for polarimetric SAR images

    Science.gov (United States)

    Uhlmann, S.; Kiranyaz, S.; Ince, T.; Gabbouj, M.

    2011-11-01

    In this paper, we introduce dynamic and scalable Synthetic Aperture Radar (SAR) terrain classification based on the Collective Network of Binary Classifiers (CNBC). The CNBC framework is primarily adapted to maximize the SAR classification accuracy on dynamically varying databases where variations do occur in any time in terms of (new) images, classes, features and users' relevance feedback. Whenever a "change" occurs, the CNBC dynamically and "optimally" adapts itself to the change by means of its topology and the underlying evolutionary method MD PSO. Thanks to its "Divide and Conquer" type approach, the CNBC can also support varying and large set of (PolSAR) features among which it optimally selects, weighs and fuses the most discriminative ones for a particular class. Each SAR terrain class is discriminated by a dedicated Network of Binary Classifiers (NBC), which encapsulates a set of evolutionary Binary Classifiers (BCs) discriminating the class with a distinctive feature set. Moreover, with each incremental evolution session, new classes/features can be introduced which signals the CNBC to create new corresponding NBCs and BCs within to adapt and scale dynamically to the change. This can in turn be a significant advantage when the current CNBC is used to classify multiple SAR images with similar terrain classes since no or only minimal (incremental) evolution sessions are needed to adapt it to a new classification problem while using the previously acquired knowledge. We demonstrate our proposed classification approach over several medium and highresolution NASA/JPL AIRSAR images applying various polarimetric decompositions. We evaluate and compare the computational complexity and classification accuracy against static Neural Network classifiers. As CNBC classification accuracy can compete and even surpass them, the computational complexity of CNBC is significantly lower as the CNBC body supports high parallelization making it applicable to grid

  2. A novel SAR fusion image segmentation method based on triplet Markov field

    Science.gov (United States)

    Wang, Jiajing; Jiao, Shuhong; Sun, Zhenyu

    2015-03-01

    Markov random field (MRF) has been widely used in SAR image segmentation because of the advantage of directly modeling the posterior distribution and suppresses the speckle on the influence of the segmentation result. However, when the real SAR images are nonstationary images, the unsupervised segmentation results by MRF can be poor. The recent proposed triplet Markov field (TMF) model is well appropriate for nonstationary SAR image processing due to the introduction of an auxiliary field which reflects the nonstationarity. In addition, on account of the texture features of SAR image, a fusion image segmentation method is proposed by fusing the gray level image and texture feature image. The effectiveness of the proposed method in this paper is demonstrated by a synthesis SAR image and the real SAR images segmentation experiments, and it is better than the state-of-art methods.

  3. Parameterized first-guess spectrum method for retrieving directional spectrum of swell-dominated waves and huge waves from SAR images

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method (PFSM), was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of the retrieving model generally used. In this method, with additional information and satellite parameters, the separating wave-number is first calculated to determine the maximum wave-number beyond which the linear relation can be used. The separating wave-number can be calculated using the additional information on wind velocity and parameters of SAR satellite. And then the SAR spectrum can be divided into SAR spectrum of wind wave and of swell according to the result of separating wave-number. The portion of SAR spectrum generated by wind wave, is used to search for the most suitable parameters of ocean wind wave spectrum, including propagation direction of ocean wave, phase speed of dominating wave and the angle spreading coefficient. The swell spectrum is acquired by directly inversing the linear relation of ocean wave spectrum to SAR spectrum given the portion of SAR spectrum generated by swell. We used the proposed method to retrieve the ocean wave spectrum from ERS-SAR data from the South China Sea and compared the result with altimeter data. The agreement indicates that the PFSM is reliable.

  4. Indonesia coverage simulation of SAR satellite at near-equatorial orbit

    Science.gov (United States)

    Septanto, Harry; Utama, Satriya; Heru Triharjanto, Robertus; Suhermanto

    2017-01-01

    Properties of SAR (Synthetic Aperture Radar) that able to penetrate the cloud and does not depend on the sunlight are a number of advantages when utilized for monitoring tropical region like the IMC (Indonesian Maritime Continent). Moreover, since having areas along equatorial belt, the IMC is at a shortcoming from perspective of highly inclined LEO (Low Earth Orbit) satellite. It would result shorter and infrequent pass times when compared with a near-equatorial LEO satellite whose low inclination. This paper reports on the investigation of a near-equatorial LEO SAR satellite coverage property through simulations. The simulations is run in nine scenarios of orbit parameter that consist of combinations of attitude {500 km, 600 km, 700 km} and inclination {80, 90, 100}. The target area is defined as 50 km x 50 km around Jakarta. Meanwhile, the SAR sensor simulation is run with swath width of 40 km, incidence angle around 250-290 and Stripmap mode. Minimum, Maximum and Mean Access Revisit of the target for each scenarios are resulted.

  5. Interferometric SAR imaging by transmitting stepped frequency chaotic noise signals

    Science.gov (United States)

    Zhang, Yunhua; Gu, Xiang; Zhai, Wenshuai; Dong, Xiao; Shi, Xiaojin; Kang, Xueyan

    2015-10-01

    Noise radar has been applied in many fields since it was proposed more than 50 years ago. However, it has not been applied to interferometric SAR imaging yet as far as we know. This paper introduces our recent work on interferometric noise radar. An interferometric SAR system was developed which can transmit both chirp signal and chaotic noise signal (CNS) at multiple carrier frequencies. An airborne experiment with this system by transmitting both signals was carried out, and the data were processed to show the capability of interferometric SAR imaging with CNS. The results shows that although the interferometric phase quality of CNS is degraded due to the signal to noise ratio (SNR) is lower compared with that of chirp signal, we still can get satisfied DEM after multi-looking processing. Another work of this paper is to apply compressed sensing (CS) theory to the interferometric SAR imaging with CNS. The CS theory states that if a signal is sparse, then it can be accurately reconstructed with much less sampled data than that regularly required according to Nyquist Sampling Theory. To form a structured random matrix, if the transmitted signal is of fixed waveform, then random subsampling is needed. However, if the transmitted signal is of random waveform, then only uniform subsampling is needed. This is another advantage of noise signal. Both the interferometric phase images and the DEMs by regular method and by CS method are processed with results compared. It is shown that the degradation of interferometric phases due to subsampling is larger than that of amplitude image.

  6. SAR image regularization with fast approximate discrete minimization.

    Science.gov (United States)

    Denis, Loïc; Tupin, Florence; Darbon, Jérôme; Sigelle, Marc

    2009-07-01

    Synthetic aperture radar (SAR) images, like other coherent imaging modalities, suffer from speckle noise. The presence of this noise makes the automatic interpretation of images a challenging task and noise reduction is often a prerequisite for successful use of classical image processing algorithms. Numerous approaches have been proposed to filter speckle noise. Markov random field (MRF) modelization provides a convenient way to express both data fidelity constraints and desirable properties of the filtered image. In this context, total variation minimization has been extensively used to constrain the oscillations in the regularized image while preserving its edges. Speckle noise follows heavy-tailed distributions, and the MRF formulation leads to a minimization problem involving nonconvex log-likelihood terms. Such a minimization can be performed efficiently by computing minimum cuts on weighted graphs. Due to memory constraints, exact minimization, although theoretically possible, is not achievable on large images required by remote sensing applications. The computational burden of the state-of-the-art algorithm for approximate minimization (namely the alpha -expansion) is too heavy specially when considering joint regularization of several images. We show that a satisfying solution can be reached, in few iterations, by performing a graph-cut-based combinatorial exploration of large trial moves. This algorithm is applied to joint regularization of the amplitude and interferometric phase in urban area SAR images.

  7. Multiscale MRF-based Texture Segmentation of SAR Image

    Institute of Scientific and Technical Information of China (English)

    XUXin; LIDeren; SUNHong

    2004-01-01

    We propose a multiscale Bayesian segmentation algorithm for SAR image in this paper. A hierarchical two-level Markov random field (MRF) is applied to represent both texture and region label over the wavelet lattice. The high level uses an isotropic Multi-level logistic (MLL) random field to characterize the blob-like region formation process at each scale and the interscale dependencies over the corresponding multiresolution region. At lower level a novel Causal Gaussian autoregressive (CGAR) process is proposed to describe the fill-in of multiresolution region. Once the multiscale double MRFs model is established, in term of Sequential maximum a posteriori (SMAP), model parameter estimate and region segmentation are performed alternately from coarse to fine scale. Our segmentation method is tested on both synthetic and ERS-1 SAR images.

  8. Sparse representation-based spectral clustering for SAR image segmentation

    Science.gov (United States)

    Zhang, Xiangrong; Wei, Zhengli; Feng, Jie; Jiao, Licheng

    2011-12-01

    A new method, sparse representation based spectral clustering (SC) with Nyström method, is proposed for synthetic aperture radar (SAR) image segmentation. Different from the conventional SC, this proposed technique is developed by using the sparse coefficients which obtained by solving l1 minimization problem to construct the affinity matrix and the Nyström method is applied to alleviate the segmentation process. The advantage of our proposed method is that we do not need to select the scaling parameter in the Gaussian kernel function artificially. We apply the proposed method, k-means and the classic spectral clustering algorithm with Nyström method to SAR image segmentation. The results show that compared with the other two methods, the proposed method can obtain much better segmentation results.

  9. Underwater topography detection of Shuangzi Reefs with SAR images acquired in different time

    Institute of Scientific and Technical Information of China (English)

    YANG Jungang; ZHANG Jie; MENG Junmin

    2007-01-01

    Imaging mechanism of underwater topography by SAR and a underwater topography SAR detection model built on the theory of underwater topography detection with SAR image presented by Yuan Yeli are used to detect the underwater topography of Shuangzi Reefs in the Nansha Islands with three scenes of SAR images acquired in different time. Detection results of three SAR images are compared with the chart topography and the detection errors are analyzed. Underwater topography detection experiments of Shuangzi Reefs show that the detection model is practicable. The detection results indicate that SAR images acquired in different time also can be used to detect the underwater topography, and the detection results are affected by the ocean conditions in the SAR acquiring time.

  10. EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

    Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

  11. A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

    Science.gov (United States)

    Vickers, H.; Eckerstorfer, M.; Malnes, E.; Larsen, Y.; Hindberg, H.

    2016-11-01

    Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide.

  12. Circular SAR Optimization Imaging Method of Buildings

    Directory of Open Access Journals (Sweden)

    Wang Jian-feng

    2015-12-01

    Full Text Available The Circular Synthetic Aperture Radar (CSAR can obtain the entire scattering properties of targets because of its great ability of 360° observation. In this study, an optimal orientation of the CSAR imaging algorithm of buildings is proposed by applying a combination of coherent and incoherent processing techniques. FEKO software is used to construct the electromagnetic scattering modes and simulate the radar echo. The FEKO imaging results are compared with the isotropic scattering results. On comparison, the optimal azimuth coherent accumulation angle of CSAR imaging of buildings is obtained. Practically, the scattering directions of buildings are unknown; therefore, we divide the 360° echo of CSAR into many overlapped and few angle echoes corresponding to the sub-aperture and then perform an imaging procedure on each sub-aperture. Sub-aperture imaging results are applied to obtain the all-around image using incoherent fusion techniques. The polarimetry decomposition method is used to decompose the all-around image and further retrieve the edge information of buildings successfully. The proposed method is validated with P-band airborne CSAR data from Sichuan, China.

  13. Compressive SAR Imaging with Joint Sparsity and Local Similarity Exploitation

    Directory of Open Access Journals (Sweden)

    Fangfang Shen

    2015-02-01

    Full Text Available Compressive sensing-based synthetic aperture radar (SAR imaging has shown its superior capability in high-resolution image formation. However, most of those works focus on the scenes that can be sparsely represented in fixed spaces. When dealing with complicated scenes, these fixed spaces lack adaptivity in characterizing varied image contents. To solve this problem, a new compressive sensing-based radar imaging approach with adaptive sparse representation is proposed. Specifically, an autoregressive model is introduced to adaptively exploit the structural sparsity of an image. In addition, similarity among pixels is integrated into the autoregressive model to further promote the capability and thus an adaptive sparse representation facilitated by a weighted autoregressive model is derived. Since the weighted autoregressive model is inherently determined by the unknown image, we propose a joint optimization scheme by iterative SAR imaging and updating of the weighted autoregressive model to solve this problem. Eventually, experimental results demonstrated the validity and generality of the proposed approach.

  14. Decreasing range resolution of a SAR image to permit correction of motion measurement errors beyond the SAR range resolution

    Science.gov (United States)

    Doerry, Armin W.; Heard, Freddie E.; Cordaro, J. Thomas

    2010-07-20

    Motion measurement errors that extend beyond the range resolution of a synthetic aperture radar (SAR) can be corrected by effectively decreasing the range resolution of the SAR in order to permit measurement of the error. Range profiles can be compared across the slow-time dimension of the input data in order to estimate the error. Once the error has been determined, appropriate frequency and phase correction can be applied to the uncompressed input data, after which range and azimuth compression can be performed to produce a desired SAR image.

  15. Study of a passive companion microsatellite to the SAOCOM-1B satellite of Argentina, for bistatic and interferometric SAR applications

    Science.gov (United States)

    Barbier, Christian; Derauw, Dominique; Orban, Anne; Davidson, Malcolm W. J.

    2014-10-01

    We report the results of a preparatory study aimed at exploring candidate applications that could benefit from a passive micro-satellite accompanying the L-band SAOCOM-1B satellite of Argentina, and to carry out a limited demonstration, based on data acquired during ESA airborne campaigns, of selected applications. In a first step of the study, the potential applications were identified and prioritized based on the mission context and strategic applications, scientific need, and feasibility. The next step of the study was to carry out some demonstrations using data sets acquired during the BioSAR 2007-2009, TropiSAR 2009 and IceSAR 2007 campaigns. A P-band InSAR digital elevation model was generated from BioSAR 2007 data. Time-series of interferometric coherence maps were obtained as a tool for change detection and monitoring. PolInSAR processing was carried out on BioSAR 2007 and IceSAR data.

  16. Radar image preprocessing. [of SEASAT-A SAR data

    Science.gov (United States)

    Frost, V. S.; Stiles, J. A.; Holtzman, J. C.; Held, D. N.

    1980-01-01

    Standard image processing techniques are not applicable to radar images because of the coherent nature of the sensor. Therefore there is a need to develop preprocessing techniques for radar images which will then allow these standard methods to be applied. A random field model for radar image data is developed. This model describes the image data as the result of a multiplicative-convolved process. Standard techniques, those based on additive noise and homomorphic processing are not directly applicable to this class of sensor data. Therefore, a minimum mean square error (MMSE) filter was designed to treat this class of sensor data. The resulting filter was implemented in an adaptive format to account for changes in local statistics and edges. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure was the result of this study. Digitally correlated Seasat-A synthetic aperture radar (SAR) imagery was used to test the technique.

  17. Persistent scatterers detection on synthetic aperture radar images acquired by Sentinel-1 satellite

    Science.gov (United States)

    Dǎnişor, Cosmin; Popescu, Anca; Datcu, Mihai

    2016-12-01

    Persistent Scatterers Interferometry (PS-InSAR) has become a popular method in remote sensing because of its capability to measure terrain deformations with very high accuracy. It relies on multiple Synthetic Aperture Radar (SAR) acquisitions, to monitor points with stable proprieties over time, called Persistent Scatterers (PS)[1]. These points are unaffected by temporal decorrelation, therefore by analyzing their interferometric phase variation we can estimate the scene's deformation rates within a given time interval. In this work, we apply two incoherent detection algorithms to identify Persistent Scatterers candidates in the city of Focșani, Romania. The first method studies the variation of targets' intensities along the SAR acquisitions and the second method analyzes the spectral proprieties of the scatterers. The algorithms were implemented on a dataset containing 11 complex images of the region covering Buzău, Brăila and Focșani cities. Images were acquired by Sentinel-1 satellite in a time span of 5 months, from October 2014 to February 2015. The processing chain follows the requirements imposed by the new C-band SAR images delivered by the Sentinel-1 satellite (launched in April 2014) imaging in Interferometric Wide (IW) mode. Considering the particularities of the TOPS (Terrain Observation with Progressive Scans in Azimuth) imaging mode[2], special requirements had to be considered for pre-processing steps. The PS detection algorithms were implemented in Gamma RS program, a software which contains various function packages dedicated to SAR images focalization, analysis and processing.

  18. Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring

    Directory of Open Access Journals (Sweden)

    Pauline Dusseux

    2014-06-01

    Full Text Available The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four optical and five SAR satellite images with high/very high spatial resolutions acquired during the growing season. A vegetation index, namely the NDVI (Normalized Difference Vegetation Index, and two biophysical variables, the LAI (Leaf Area Index and the fCOVER (fraction of Vegetation Cover were computed using optical time series and polarization (HH, VV, HV, VH. The polarization ratio and polarimetric decomposition (Freeman–Durden and Cloude–Pottier were calculated using SAR time series. Then, variables derived from optical, SAR and both types of remotely-sensed data were successively classified using the Support Vector Machine (SVM technique. The results show that the classification accuracy of SAR variables is higher than those using optical data (0.98 compared to 0.81. They also highlight that the combination of optical and SAR time series data is of prime interest to discriminate grasslands from crops, allowing an improved classification accuracy.

  19. A detection model of underwater topography with a series of SAR images acquired at different time

    Institute of Scientific and Technical Information of China (English)

    YANG Jungang; ZHANG Jie; MENG Junmin

    2010-01-01

    underwater topography is one of oceanic features detected by Synthetic Aperture Radar. Under-water topography SAR imaging mechanism shows that tidal current is the important factor for underwater topography SAR imaging. Thus under the same wind field condition, SAR images for the same area acquired at different time include different information of the underwater topogra-phy. To utilize synchronously SAR images acquired at different time for the underwater topography SAR detection and improve the precision of detection, based on the detection model of underwater topography with single SAR image and the periodicity of tidal current, a detection model of under- water topography with a series of SAR images acquired at different time is developed by combing with tide and tidal current numerical simulation. To testify the feasibility of the presented model, Taiwan Shoal located at the south outlet of Taiwan Strait is selected as study area and three SAR images are used in the underwater topography detection. The detection results are compared with the field observation data of water depth carried out by R/V Dongfanghong 2, and the errors of the detection are compared with those of the single SAR image. All comparisons show that the detec- tion model presented in the paper improves the precision of underwater topography SAR detection, and the presented model is feasible.

  20. SAR image segmentation using MSER and improved spectral clustering

    Science.gov (United States)

    Gui, Yang; Zhang, Xiaohu; Shang, Yang

    2012-12-01

    A novel approach is presented for synthetic aperture radar (SAR) image segmentation. By incorporating the advantages of maximally stable extremal regions (MSER) algorithm and spectral clustering (SC) method, the proposed approach provides effective and robust segmentation. First, the input image is transformed from a pixel-based to a region-based model by using the MSER algorithm. The input image after MSER procedure is composed of some disjoint regions. Then the regions are treated as nodes in the image plane, and a graph structure is applied to represent them. Finally, the improved SC is used to perform globally optimal clustering, by which the result of image segmentation can be generated. To avoid some incorrect partitioning when considering each region as one graph node, we assign different numbers of nodes to represent the regions according to area ratios among the regions. In addition, K-harmonic means instead of K-means is applied in the improved SC procedure in order to raise its stability and performance. Experimental results show that the proposed approach is effective on SAR image segmentation and has the advantage of calculating quickly.

  1. A Level Set Filter for Speckle Reduction in SAR Images

    Directory of Open Access Journals (Sweden)

    Xiaoxia Huang

    2010-01-01

    Full Text Available Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

  2. A Level Set Filter for Speckle Reduction in SAR Images

    Science.gov (United States)

    Li, Hongga; Huang, Bo; Huang, Xiaoxia

    2010-12-01

    Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

  3. Analysis of Geosynchronous Satellite-air Bistatic SAR Clutter Characteristics from the Point of View of Ground Moving Target Indication

    Directory of Open Access Journals (Sweden)

    Zhang Dan-dan

    2013-09-01

    Full Text Available Under the geometry of geosynchronous satellite-air bistatic SAR where the geosynchronous satellite is the transmitter and aerostat is the receiver, in order to suppress clutter and detect slowly moving target using Space Time Adaptive Processing (STAP, it is necessary to analyze the clutter characteristics. From the point of view of ground moving target indication, the theory model of the clutter characteristics under the geometry of geosynchronous satellite-space bistatic SAR is analyzed and established in this paper; especially, the range-dependence characteristics of the angle-Doppler curve of the clutter is analyzed. Finally, the simulation verifies correctness of the analysis. The theory model and the conclusion in this paper indicates the clutter characteristics of the new geosynchronous satellite-air bistatic SAR mode, and provide theory basis for the selection and research of ground moving target indication method under this mode.

  4. Terrain Imaging Using a SAR System Based on Reflected GPS Signals

    Institute of Scientific and Technical Information of China (English)

    Li Yong-hong; C. Rizos; E. Donskoi; J. Homer; B. Mojarrabi

    2003-01-01

    This paper describes a 3D multi-static synthetic aperture radar (SAR) imaging system which utilises reflected GPS signals from moving objects on the Earth's surface. The principle of bi-static radar is used to model the reflected GPS signals. The movement of a visible GPS satellite serves as a base for a synthetic aperture over an observation time period. As an example, a MATLAB simulation has been carried out in order to detect the movement of imaged object sunder the assumption of one static GPS receiver with two targets which move with different speeds. The influence of the visible satellite'sposition and velocity on the spatial resolution of such a SAR system isdiscussed. Simulation results show that by measuring the cross-correlation of the reflected GPS signal from the terrain and objects on it,the detection of the objects can enjoy a good spatial resolution for thecase of moving objects and a moving GPS receiver. Furthermore, thespatial resolution is also related to the selection of visible GPS satelliteswith respect to their azimuths, elevations and velocities. This systemhas the following useful features: (a) no dedicated signal transmitter is required; (b) the GPS signal frequency is reused; (c) GPS operates round-the-clock and its signals cover the entire Earth's surface; (d) low power consumption; and (e) known GPS signal structure.

  5. Automatic Registration of SAR Images with the Integrated Complementary Invariant Feature

    Directory of Open Access Journals (Sweden)

    Xiao-hua Wang

    2014-01-01

    Full Text Available The accurate Synthetic Aperture Radar (SAR image registration is important for exact analyses of mine deformation and ecological environment change. Currently, many image registration algorithms have been proposed, but these registration algorithms cannot be directly applied to SAR image, so an integrated registration approach is presented in this paper. Firstly, it is the coarse matching with Canny edge dividing regions; secondly, it is the fine matching by SIFT algorithm with improved Canny edge features; finally, obtain accurate registration SAR image. This approach has fewer computations than that simply using SIFT feature matching. Experimental analyses with SAR images of Yanzhou Mine demonstrate the efficiency and the accuracy of this approach for mine SAR image registration, which provides a simple and effective tool in SAR monitoring of mining deformation and ecological changes

  6. Scalable Track Detection in SAR CCD Images

    Energy Technology Data Exchange (ETDEWEB)

    Chow, James G [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Quach, Tu-Thach [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.

  7. Method of airborne SAR image match integrating multi-information for block adjustment

    Science.gov (United States)

    Yang, S. C.; Huang, G. M.; Zhao, Z.; Lu, L. J.

    2015-06-01

    For the automation of SAR image Block Adjustment, this paper proposed a method of SAR image matching integrating multiinformation. It takes full advantage of SAR image geometric information, feature information, gray-related information and external auxiliary terrain information for SAR image matching. And then Image Tie Points (ITPs) of Block Adjustment can be achieved automatically. The main parts of extracting ITPs automatically include: First, SAR images were rectified geometrically based on the geometric information and external auxiliary terrain information (existed DEM) before match. Second, ground grid points with a certain interval can be get in the block area and approximate ITPs were acquired based on external auxiliary terrain information. Then match reference point was extracted for homologous image blocks with Harris feature detection operator and ITPs were obtained with pyramid matching based on gray-related information. At last, ITPs were transferred from rectified images to original SAR images and used in block adjustment. In the experiment, X band airborne SAR images acquired by Chinese airborne SAR system - CASMSAR system were used to make up the block. The result had showed that the method is effective for block adjustment of SAR data.

  8. Ubiquitous and continuous SAR imaging for natural hazards: present and future of remote sensing

    Science.gov (United States)

    Monti Guarnieri, Andrea; Rocca, Fabio

    2017-04-01

    Constellation of optical and SAR sensors have achieved unprecedented performances: dense constellation of cubesats - like the next constellation of 88 Dove satellites (Planet labs), launched simultaneously this February - reduce the revisit time to nearly daily. This brings great value to many domains, like the assessment of risk and damage in natural hazards, post-earthquake response, real time flood monitoring. The limits to optical imaging due to cloud coverage could then be removed with drones. Alternatively, decades of coherent exploitation of Synthetic Aperture Radars have demonstrated their unique capabilities in precise deformation monitoring, penetration in canopies and subsurfaces (glacier and deserts), 3D imaging of volumes, sensitivity to soil moisture and generation of water vapor maps. Thanks to these capabilities, for one, early warning was possible for a landslide at Bingham Canyon Mine (one of the largest in history), whereas monitoring of infrastructures, natural gas and carbon dioxide storage reservoirs, dams, mines is already an established business. Many of these applications are made possible by the Sentinel-1 SAR constellation, the first to provide systematic coherent acquisitions and free and open data. More than 50000 products are downloaded daily. Nonetheless, the present revisit times of this constellation (1-3 days), or the future 6 hours of Cosmo-SKYmed I and II constellations, will leave a gap that cannot be fruitfully exploited for early warning of landslides, real time mapping of flooding, hydrometeor forecasts, real-time regional alerts of collapse, continuous soil moisture mapping for precision farming. On the other side, the limited penetration capabilities of C-band (Sentinel-1) and X band (Cosmo, TerraSAR constellations) would not allow sufficient penetration to monitor volumes, like ice, sands and forests. In order to fill these gaps, two novel SAR systems are under study and will possibly appear in the next decades

  9. A novel method for multi-angle SAR image matching

    Institute of Scientific and Technical Information of China (English)

    Li Dapeng

    2015-01-01

    Multi-angle synthetic aperture radar (SAR) image matching is very challenging, because the same object may cause different backscattering patterns, heavily depending on the radar incident angle. A technique based on the relations between the invariant positions of ground targets among the reference and sensed images is proposed to accommodate the nonmatching patterns. It involves a target extraction using wavelet coefficient fusion, as well as a geometric voting matching routine for searching the matched control points (CPs) in the reference and sensed images, respec-tively. To accelerate the speed of the search, a robust, rapidly corresponding CPs determination strategy is exploited by utilizing the global spatial transformation model, as well as a procedure of outlier removal to ensure the desired accuracy. Meanwhile, the positions of the matched point pairs are relocated using mutual information. The final warping of the images according to the CPs is performed by using a polynomial function. The results show the possibility of matching multi-angle SAR images in general cases.

  10. A high-resolution, four-band SAR testbed with real-time image formation

    Energy Technology Data Exchange (ETDEWEB)

    Walker, B.; Sander, G.; Thompson, M.; Burns, B.; Fellerhoff, R.; Dubbert, D.

    1996-03-01

    This paper describes the Twin-Otter SAR Testbed developed at Sandia National Laboratories. This SAR is a flexible, adaptable testbed capable of operation on four frequency bands: Ka, Ku, X, and VHF/UHF bands. The SAR features real-time image formation at fine resolution in spotlight and stripmap modes. High-quality images are formed in real time using the overlapped subaperture (OSA) image-formation and phase gradient autofocus (PGA) algorithms.

  11. Forecasting Hurricane by Satellite Image

    Science.gov (United States)

    Liu, M. Y.

    Earth is an endanger planet. Severe weather, especially hurricanes, results in great disaster all the world. World Meteorology Organization and United Nations Environment Program established intergovernment Panel on Climate Change (IPCC) to offer warnings about the present and future disasters of the Earth. It is the mission for scientists to design warning system to predict the severe weather system and to reduce the damage of the Earth. Hurricanes invade all the world every year and made millions damage to all the people. Scientists in weather service applied satellite images and synoptic data to forecast the information for the next hours for warning purposes. Regularly, hurricane hits on Taiwan island directly will pass through her domain and neighbor within 10 hours. In this study, we are going to demonstrate a tricky hurricane NARI invaded Taiwan on September 16, 2000. She wandered in the neighborhood of the island more than 72 hours and brought heavy rainfall over the island. Her track is so tricky that scientists can not forecast her path using the regular method. Fortunately, all scientists in the Central Weather Bureau paid their best effort to fight against the tricky hurricane. Applying the new developed technique to analysis the satellite images with synoptic data and radar echo, scientists forecasted the track, intensity and rainfall excellently. Thus the damage of the severe weather reduced significantly.

  12. A new strategic sampling for offshore wind assessment using radar satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Beaucage, P.; Lafrance, G.; Bernier, M.; Lafrance, J. [Institut National de la Recherche Scientifique, Varennes, PQ (Canada); Choisnard, J. [Hydro-Quebec, Varennes, PQ (Canada)

    2007-07-01

    Synthetic Aperture Radar (SAR) satellite images have been used for offshore wind assessment. Several offshore wind farms are in operation or under construction in northern Europe. The European target for 2030 is 300 GW, of which half is intended for onshore and half for offshore development. Offshore projects in the east coast United States, the Gulf of Mexico and west coast of Canada are in the planning stage. Information obtained from SAR can be used to supplement current mapping methods of offshore wind energy resources. SAR is a useful tool to localize wind pattern over water surfaces. Other sources of offshore wind observations include meteorological stations such as buoys and masts; remote sensing instruments onboard satellites such as scatterometers (QuikSCAT, ASCAT) or passive microwave radiometers; and numerical weather prediction models. The synergy between scatterometers and SAR was discussed. The SAR system has been used for microscale resolution wind mapping in the Gaspe Peninsula. Strategic sampling zones were chosen in proximity to the QuikSCAT grid. It was concluded that 270 and 570 SAR images are needed to calculate average wind speed (U) and mean power output of a 3 MW wind turbine (P) over the Gaspe Peninsula region, respectively. It was concluded that microscale regional wind mapping can be produced at a lower cost with strategic sampling compared to random sampling. refs., tabs., figs.

  13. Color fusion of SAR and FLIR images using a natural color transfer technique

    Institute of Scientific and Technical Information of China (English)

    Shaoyuan Sun; Zhongliang Jing; Zhenhua Li; Gang Liu

    2005-01-01

    Fusion of synthetic aperture radar (SAR) and forward looking infrared (FLIR) images is an important subject for aerospace and sensor surveillance. This paper presents a scheme to achieve a natural color image based on the contours feature of SAR and the target region feature of FLIR so that the overall scene recognition and situational awareness can be improved. The SAR and FLIR images are first decomposed into steerable pyramids, and the contour maps in the SAR image and the region maps in the FLIR image are calculated. The contour and region features are fused at each level of the steerable pyramids. A color image is then formed by transferring daytime color to the monochromic image by using the natural color transfer technique. Experimental results show that the proposed method is effective in providing a color fusion of SAR and FLIR images.

  14. A learning tool for optical and microwave satellite image processing and analysis

    Science.gov (United States)

    Dashondhi, Gaurav K.; Mohanty, Jyotirmoy; Eeti, Laxmi N.; Bhattacharya, Avik; De, Shaunak; Buddhiraju, Krishna M.

    2016-04-01

    This paper presents a self-learning tool, which contains a number of virtual experiments for processing and analysis of Optical/Infrared and Synthetic Aperture Radar (SAR) images. The tool is named Virtual Satellite Image Processing and Analysis Lab (v-SIPLAB) Experiments that are included in Learning Tool are related to: Optical/Infrared - Image and Edge enhancement, smoothing, PCT, vegetation indices, Mathematical Morphology, Accuracy Assessment, Supervised/Unsupervised classification etc.; Basic SAR - Parameter extraction and range spectrum estimation, Range compression, Doppler centroid estimation, Azimuth reference function generation and compression, Multilooking, image enhancement, texture analysis, edge and detection. etc.; SAR Interferometry - BaseLine Calculation, Extraction of single look SAR images, Registration, Resampling, and Interferogram generation; SAR Polarimetry - Conversion of AirSAR or Radarsat data to S2/C3/T3 matrix, Speckle Filtering, Power/Intensity image generation, Decomposition of S2/C3/T3, Classification of S2/C3/T3 using Wishart Classifier [3]. A professional quality polarimetric SAR software can be found at [8], a part of whose functionality can be found in our system. The learning tool also contains other modules, besides executable software experiments, such as aim, theory, procedure, interpretation, quizzes, link to additional reading material and user feedback. Students can have understanding of Optical and SAR remotely sensed images through discussion of basic principles and supported by structured procedure for running and interpreting the experiments. Quizzes for self-assessment and a provision for online feedback are also being provided to make this Learning tool self-contained. One can download results after performing experiments.

  15. Oil spill detection from SAR image using SVM based classification

    Directory of Open Access Journals (Sweden)

    A. A. Matkan

    2013-09-01

    Full Text Available In this paper, the potential of fully polarimetric L-band SAR data for detecting sea oil spills is investigated using polarimetric decompositions and texture analysis based on SVM classifier. First, power and magnitude measurements of HH and VV polarization modes and, Pauli, Freeman and Krogager decompositions are computed and applied in SVM classifier. Texture analysis is used for identification using SVM method. The texture features i.e. Mean, Variance, Contrast and Dissimilarity from them are then extracted. Experiments are conducted on full polarimetric SAR data acquired from PALSAR sensor of ALOS satellite on August 25, 2006. An accuracy assessment indicated overall accuracy of 78.92% and 96.46% for the power measurement of the VV polarization and the Krogager decomposition respectively in first step. But by use of texture analysis the results are improved to 96.44% and 96.65% quality for mean of power and magnitude measurements of HH and VV polarizations and the Krogager decomposition. Results show that the Krogager polarimetric decomposition method has the satisfying result for detection of sea oil spill on the sea surface and the texture analysis presents the good results.

  16. MERGING AIRBORNE LIDAR DATA AND SATELLITE SAR DATA FOR BUILDING CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    T. Yamamoto

    2015-05-01

    Full Text Available A frequent map revision is required in GIS applications, such as disaster prevention and urban planning. In general, airborne photogrammetry and LIDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, attribute data acquisition and classification depend on manual editing works including ground surveys. In general, airborne photogrammetry and LiDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, these approaches classify geometrical attributes. Moreover, ground survey and manual editing works are finally required in attribute data classification. On the other hand, although geometrical data extraction is difficult, SAR data have a possibility to automate the attribute data acquisition and classification. The SAR data represent microwave reflections on various surfaces of ground and buildings. There are many researches related to monitoring activities of disaster, vegetation, and urban. Moreover, we have an opportunity to acquire higher resolution data in urban areas with new sensors, such as ALOS2 PALSAR2. Therefore, in this study, we focus on an integration of airborne LIDAR data and satellite SAR data for building extraction and classification.

  17. Azimuth resolution improvement for spaceborne SAR images with quasi-non-overlapped Doppler bandwidth

    Institute of Scientific and Technical Information of China (English)

    Zheng Bao

    2014-01-01

    The azimuth resolution improvement problem is solved via a coherent combination of synthetic aperture radar (SAR) ima-ges with the quasi-non-overlapped Doppler bandwidth. Prior to the spectra combination, SAR images should be co-registered, while phase biases induced by topography, atmospheric propagation de-lays and baseline measurement errors should be calibrated. How-ever, the coregistration accuracy suffers from large Doppler decorrelation caused by the quasi-non-overlapped Doppler band-width. Furthermore, the method used to estimate phase biases from interferogram of azimuth pre-filtered SAR image pairs wil fail when there is no overlapped spectrum. The fringe simulation and maximum sharpness optimization are adopted to deal with the problems. Accordingly, a novel algorithm to coherently synthesize SAR images is presented. The experiment with the Terra SAR X-band (TerraSAR-X) satel ite data validates the performance of the presented method.

  18. Integration of SAR features into multispectral images based on the nonsubsampled contourlet and IHS transform

    Science.gov (United States)

    Yang, Zhixiang; He, Xiufeng; Xu, Jia

    2011-10-01

    As a new image multiscale geometric analysis tool, the nonsubsampled contourlet transform (NSCT) has many advantages such as multiscale, localization and multidirection, and can efficiently capture the geometric information of images. Therefore, when the NSCT is introduced to image fusion, the characteristics of original images can be taken better and more information for fusion can be obtained. In this paper, a novel fusion algorithm for fusion of the synthetic aperture radar (SAR) image and multispectral images using conjointly the intensity-hue-saturation (IHS) transform and NSCT is proposed. In the proposed method, atrous wavelet is adopted to extract the detail information in low frequency parts fusion, and a new salience measure named as local inner product is introduced to select the high frequency coefficients. A PALSAR HH image of ALOS satellite despeckled by the Lee-sigma filter and HJ-1 multispectral images are used to evaluate the performance and efficiency of the proposed method. The fused images of each method are evaluated by qualitative and quantitative comparison and analysis compared with some traditional fusion rules. The experimental results indicate that the proposed method has the merits of better preservation of image definition and less loss of spectral information.

  19. SAR and Oblique Aerial Optical Image Fusion for Urban Area Image Segmentation

    Science.gov (United States)

    Fagir, J.; Schubert, A.; Frioud, M.; Henke, D.

    2017-05-01

    The fusion of synthetic aperture radar (SAR) and optical data is a dynamic research area, but image segmentation is rarely treated. While a few studies use low-resolution nadir-view optical images, we approached the segmentation of SAR and optical images acquired from the same airborne platform - leading to an oblique view with high resolution and thus increased complexity. To overcome the geometric differences, we generated a digital surface model (DSM) from adjacent optical images and used it to project both the DSM and SAR data into the optical camera frame, followed by segmentation with each channel. The fused segmentation algorithm was found to out-perform the single-channel version.

  20. Integrated Analysis of Interferometric SAR, Satellite Altimetry and Hydraulic Modeling to Quantify Louisiana Wetland Dynamics

    Science.gov (United States)

    Lee, Hyongki; Kim, Jin-woo; Lu, Zhong; Jung, Hahn Chul; Shum, C. K.; Alsdorf, Doug

    2012-01-01

    Wetland loss in Louisiana has been accelerating due primarily to anthropogenic and nature processes, and is being advocated as a problem with national importance. Accurate measurement or modeling of wetland-wide water level changes, its varying extent, its storage and discharge changes resulting in part from sediment loads, erosion and subsidence are fundamental to assessment of hurricane-induced flood hazards and wetland ecology. Here, we use innovative method to integrate interferometric SAR (InSAR) and satellite radar altimetry for measuring absolute or geocentric water level changes and applied the methodology to remote areas of swamp forest in coastal Louisiana. Coherence analysis of InSAR pairs suggested that the HH polarization is preferred for this type of observation, and polarimetric analysis can help to identi:fy double-bonnce backscattering areas in the wetland. Envisat radar altimeter-measured 18- Hz (along-track sampling of 417 m) water level data processed with regional stackfile method have been used to provide vertical references for water bodies separated by levees. The high-resolution (approx.40 m) relative water changes measured from ALOS PALSAR L-band and Radarsat-l C-band InSAR are then integrated with Envisat radar altimetry to obtain absolute water level. The resulting water level time series were validated with in situ gauge observations within the swamp forest. Furthermore, we compare our water elevation changes with 2D flood modeling from LISFLOOD hydrodynamic model. Our study demonstrates that this new technique allows retrospective reconstruction and concurrent monitoring of water conditions and flow dynamics in wetlands, especially those lacking gauge networks.

  1. GRAY TONE FILTERING ON ERS-SAR IMAGES APPLIED TO CHANGE DETECTION AND MAPPING

    Directory of Open Access Journals (Sweden)

    Gilles André

    2011-05-01

    Full Text Available In SAR images, the pixel values are tightly related to physical parameters of the soil such as topography, roughness and humidity, regardless to atmospheric conditions. Therefore, SAR images may be used to detect, and quantify changes in land cover, by comparison of time series SAR data. Classical change detection techniques from SAR images are based on additive synthesis of RGB colors and arithmetic operations between images. The noisy aspect of ERS image due to the original speckle is an obstacle for available mapping and quantification of the changes. Here, statistical and morphological filters are used to reduce the speckle noise. Combined techniques of change detection and noise filtering are applied here to assess and map from ERS-SAR images the impact of regular or catastrophic flood and deforestation in the East Coast of Madagascar.

  2. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  3. Illicit vessel identification in inland waters using SAR image

    Science.gov (United States)

    Zhang, Fengli; Wu, Bingfang; Zhang, Lei; Huang, Huiping; Tian, Yichen

    2006-10-01

    Synthetic Aperture Radar remote sensing has been effectively used in water compliance and enforcement, especially in ship detection, but it is still very difficult to classify or identify vessels in inland water only using existing SAR image. Nevertheless some experience knowledge can help, for example waterway channel is of great significance for water traffic management and illegal activity monitoring. It can be used for judging a vessel complying with traffic rules or not, and also can be used to indicate illicit fishing vessels which are usually far away from navigable waterway channel. For illicit vessel identification speed and efficiency are very important, so it will be significant if we can extract waterway channel directly from SAR images and use it to identify illicit vessels. The paper first introduces the modified two-parameter CFAR algorithm used to detect ship targets in inland waters, and then uses principal curves and neural networks to extract waterway channel. Through comparing the detection results and the extracted waterway channel those vessels not complying with water traffic rules or potential illicit fishing vessels can be easily identified.

  4. Recognizing articulated objects and object articulation in SAR images

    Science.gov (United States)

    Bhanu, Bir; Jones, Grinnell, III; Ahn, Joon S.

    1998-09-01

    The focus of this paper is recognizing articulated objects and the pose of the articulated parts in SAR images. Using SAR scattering center locations as features, the invariance with articulation (i.e. turret rotation for the T72, T80 and M1a tanks, missile erect vs. down for the SCUD launcher) is shown as a function of object azimuth. Similar data is shown for configuration differences in the MSTAR (Public) Targets. The UCR model-based recognition engine (which uses non- articulated models to recognize articulated, occluded and non-standard configuration objects) is described and target identification performance results are given as confusion matrices and ROC curves for six inch and one foot resolution XPATCH images and the one foot resolution MSTAR data. Separate body and turret models are developed that are independent of the relative positions between the body and the turret. These models are used with a subsequent matching technique to refine the pose of the body and determine the pose of the turret. An expression of the probability that a random match will occur is derived and this function is used to set thresholds to minimize the probability of a random match for the recognition system. Results for identification, body pose and turret pose are presented as a function of percent occlusion for articulated XPATCH data and results are given for identification and body pose for articulated MSTAR data.

  5. Flight path-driven mitigation of wavefront curvature effects in SAR images

    Science.gov (United States)

    Doerry, Armin W.

    2009-06-23

    A wavefront curvature effect associated with a complex image produced by a synthetic aperture radar (SAR) can be mitigated based on which of a plurality of possible flight paths is taken by the SAR when capturing the image. The mitigation can be performed differently for different ones of the flight paths.

  6. Efficient DPCA SAR imaging with fast iterative spectrum reconstruction method

    Institute of Scientific and Technical Information of China (English)

    FANG Jian; ZENG JinShan; XU ZongBen; ZHAO Yao

    2012-01-01

    The displaced phase center antenna (DPCA) technique is an effective strategy to achieve wide-swath synthetic aperture radar (SAR) imaging with high azimuth resolution.However,traditionally,it requires strict limitation of the pulse repetition frequency (PRF) to avoid non-uniform sampling.Otherwise,any deviation could bring serious ambiguity if the data are directly processed using a matched filter.To break this limitation,a recently proposed spectrum reconstruction method is capable of recovering the true spectrum from the nonuniform samples. However,the performance is sensitive to the selection of the PRF.Sparse regularization based imaging may provide a way to overcome this sensitivity. The existing time-domain method,however,requires a large-scale observation matrix to be built,which brings a high computational cost.In this paper,we propose a frequency domain method,called the iterative spectrum reconstruction method,through integration of the sparse regularization technique with spectrum analysis of the DPCA signal.By approximately expressing the observation in the frequency domain,which is realized via a series of decoupled linear operations,the method performs SAR imaging which is then not directly based on the observation matrix,which reduces the computational cost from O(N2) to O(NlogN) (where N is the number of range cells),and is therefore more efficient than the time domain method. The sparse regularization scheme,realized via a fast thresholding iteration,has been adopted in this method,which brings the robustness of the imaging process to the PRF selection.We provide a series of simulations and ground based experiments to demonstrate the high efficiency and robustness of the method.The simulations show that the new method is almost as fast as the traditional mono-channel algorithm,and works well almost independently of the PRF selection.Consequently,the suggested method can be accepted as a practical and efficient wide-swath SAR imaging technique.

  7. a Novel Image Registration Algorithm for SAR and Optical Images Based on Virtual Points

    Science.gov (United States)

    Ai, C.; Feng, T.; Wang, J.; Zhang, S.

    2013-07-01

    Optical image is rich in spectral information, while SAR instrument can work in both day and night and obtain images through fog and clouds. Combination of these two types of complementary images shows the great advantages of better image interpretation. Image registration is an inevitable and critical problem for the applications of multi-source remote sensing images, such as image fusion, pattern recognition and change detection. However, the different characteristics between SAR and optical images, which are due to the difference in imaging mechanism and the speckle noises in SAR image, bring great challenges to the multi-source image registration. Therefore, a novel image registration algorithm based on the virtual points, derived from the corresponding region features, is proposed in this paper. Firstly, image classification methods are adopted to extract closed regions from SAR and optical images respectively. Secondly, corresponding region features are matched by constructing cost function with rotate invariant region descriptors such as area, perimeter, and the length of major and minor axes. Thirdly, virtual points derived from corresponding region features, such as the centroids, endpoints and cross points of major and minor axes, are used to calculate initial registration parameters. Finally, the parameters are corrected by an iterative calculation, which will be terminated when the overlap of corresponding region features reaches its maximum. In the experiment, WordView-2 and Radasat-2 with 0.5 m and 4.7 m spatial resolution respectively, obtained in August 2010 in Suzhou, are used to test the registration method. It is shown that the multi-source image registration algorithm presented above is effective, and the accuracy of registration is up to pixel level.

  8. A method to calibrate channel friction and bathymetry parameters of a Sub-Grid hydraulic model using SAR flood images

    Science.gov (United States)

    Wood, M.; Neal, J. C.; Hostache, R.; Corato, G.; Chini, M.; Giustarini, L.; Matgen, P.; Wagener, T.; Bates, P. D.

    2015-12-01

    Synthetic Aperture Radar (SAR) satellites are capable of all-weather day and night observations that can discriminate between land and smooth open water surfaces over large scales. Because of this there has been much interest in the use of SAR satellite data to improve our understanding of water processes, in particular for fluvial flood inundation mechanisms. Past studies prove that integrating SAR derived data with hydraulic models can improve simulations of flooding. However while much of this work focusses on improving model channel roughness values or inflows in ungauged catchments, improvement of model bathymetry is often overlooked. The provision of good bathymetric data is critical to the performance of hydraulic models but there are only a small number of ways to obtain bathymetry information where no direct measurements exist. Spatially distributed river depths are also rarely available. We present a methodology for calibration of model average channel depth and roughness parameters concurrently using SAR images of flood extent and a Sub-Grid model utilising hydraulic geometry concepts. The methodology uses real data from the European Space Agency's archive of ENVISAT[1] Wide Swath Mode images of the River Severn between Worcester and Tewkesbury during flood peaks between 2007 and 2010. Historic ENVISAT WSM images are currently free and easy to access from archive but the methodology can be applied with any available SAR data. The approach makes use of the SAR image processing algorithm of Giustarini[2] et al. (2013) to generate binary flood maps. A unique feature of the calibration methodology is to also use parameter 'identifiability' to locate the parameters with higher accuracy from a pre-assigned range (adopting the DYNIA method proposed by Wagener[3] et al., 2003). [1] https://gpod.eo.esa.int/services/ [2] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote

  9. A Likelihood-Based SLIC Superpixel Algorithm for SAR Images Using Generalized Gamma Distribution

    Directory of Open Access Journals (Sweden)

    Huanxin Zou

    2016-07-01

    Full Text Available The simple linear iterative clustering (SLIC method is a recently proposed popular superpixel algorithm. However, this method may generate bad superpixels for synthetic aperture radar (SAR images due to effects of speckle and the large dynamic range of pixel intensity. In this paper, an improved SLIC algorithm for SAR images is proposed. This algorithm exploits the likelihood information of SAR image pixel clusters. Specifically, a local clustering scheme combining intensity similarity with spatial proximity is proposed. Additionally, for post-processing, a local edge-evolving scheme that combines spatial context and likelihood information is introduced as an alternative to the connected components algorithm. To estimate the likelihood information of SAR image clusters, we incorporated a generalized gamma distribution (GГD. Finally, the superiority of the proposed algorithm was validated using both simulated and real-world SAR images.

  10. SIMULATION OF SHIP GENERATED TURBULENT AND VORTICAL WAKE IMAGING BY SAR

    Institute of Scientific and Technical Information of China (English)

    Wang Aiming; Zhu Minhui

    2004-01-01

    Synthetic Aperture Radar (SAR) imaging of ocean surface features is studied. The simulation of the turbulent and vortical features generated by a moving ship and SAR imaging of these wakes is carried out. The turbulent wake damping the ocean surface capillary waves may be partially responsible for the suppression of surface waves near the ship track. The vortex pair generating a change in the lateral flow field behind the ship may be partially responsible for an enhancement of the waves near the edges of the smooth area. These hydrodynamic phenomena as well as the changes of radar backscatter generated by turbulence and vortex are simulated.An SAR imaging model is then used on such ocean surface features to provide SAR images.Comparison of two ships' simulated SAR images shows that the wake features are different for various ship parameters.

  11. Fault and anthropogenic processes in central California constrained by satellite and airborne InSAR and in-situ observations

    Science.gov (United States)

    Liu, Zhen; Lundgren, Paul

    2016-07-01

    The San Andreas Fault (SAF) system is the primary plate boundary in California, with the central SAF (CSAF) lying adjacent to the San Joaquin Valley (SJV), a vast structural trough that accounts for about one-sixth of the United Sates' irrigated land and one-fifth of its extracted groundwater. The CSAF displays a range of fault slip behavior with creeping in its central segment that decreases towards its northwest and southeast ends, where the fault transitions to being fully locked. At least six Mw ~6.0 events since 1857 have occurred near the Parkfield transition, most recently in 2004. Large earthquakes also occurred on secondary faults parallel to the SAF, the result of distributed deformation across the plate boundary zone. Recent studies have revealed the complex interaction between anthropogenic related groundwater depletion and the seismic activity on adjacent faults through stress interaction. Despite recent progress, many questions regarding fault and anthropogenic processes in the region still remain. For example, how is the relative plate motion accommodated between the CSAF and off-fault deformation? What is the distribution of fault creep and slip deficit at shallow depths? What are the spatiotemporal variations of fault slip? What are the spatiotemporal characteristics of anthropogenic and lithospheric processes and how do they interact with each other? To address these, we combine satellite InSAR and NASA airborne UAVSAR data to image on and off-fault deformation. The UAVSAR data cover fault perpendicular swaths imaged from opposing look directions and fault parallel swaths since 2009. The much finer spatial resolution and optimized viewing geometry provide important constraints on near fault deformation and fault slip at very shallow depth. We performed a synoptic InSAR time series analysis using ERS-1/2, Envisat, ALOS and UAVSAR interferograms. The combined C-band ERS-1/2 and Envisat data provide a long time interval of SAR data over the region

  12. Ship heading and velocity analysis by wake detection in SAR images

    Science.gov (United States)

    Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo

    2016-11-01

    With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.

  13. SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

    Directory of Open Access Journals (Sweden)

    A. Rezaeian

    2015-12-01

    Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  14. Image quality specification and maintenance for airborne SAR

    Science.gov (United States)

    Clinard, Mark S.

    2004-08-01

    Specification, verification, and maintenance of image quality over the lifecycle of an operational airborne SAR begin with the specification for the system itself. Verification of image quality-oriented specification compliance can be enhanced by including a specification requirement that a vendor provide appropriate imagery at the various phases of the system life cycle. The nature and content of the imagery appropriate for each stage of the process depends on the nature of the test, the economics of collection, and the availability of techniques to extract the desired information from the data. At the earliest lifecycle stages, Concept and Technology Development (CTD) and System Development and Demonstration (SDD), the test set could include simulated imagery to demonstrate the mathematical and engineering concepts being implemented thus allowing demonstration of compliance, in part, through simulation. For Initial Operational Test and Evaluation (IOT&E), imagery collected from precisely instrumented test ranges and targets of opportunity consisting of a priori or a posteriori ground-truthed cultural and natural features are of value to the analysis of product quality compliance. Regular monitoring of image quality is possible using operational imagery and automated metrics; more precise measurements can be performed with imagery of instrumented scenes, when available. A survey of image quality measurement techniques is presented along with a discussion of the challenges of managing an airborne SAR program with the scarce resources of time, money, and ground-truthed data. Recommendations are provided that should allow an improvement in the product quality specification and maintenance process with a minimal increase in resource demands on the customer, the vendor, the operational personnel, and the asset itself.

  15. Sub-urban landscape characterization by very high-resolution X-band COSMO-Skymed SAR images: first results

    Science.gov (United States)

    Del Frate, Fabio; Loschiavo, Domenico; Pratola, Chiara; Schiavon, Giovanni; Solimini, Domenico

    2010-10-01

    The very-high spatial resolution provided by COSMO-Skymed products, also considering the concurrent TerraSAR-X mission, opens new challenges in the field of SAR image processing for remote sensing applications, maybe comparable to those represented by the first optical commercial satellites at the beginning of last decade. The Tor Vergata-Frascati test site, where extensive ground-truth data are available, was imaged by the COSMO constellation at two different days in summer 2010. This enabled first investigations on the potential of this type of imagery in providing a characterization of sub-urban areas by exploitation of both amplitude and phase information contained in the radar return. In particular this paper deals with the set-up of preliminary chains of automatic processing based on Multi-Layer Perceptron neural networks for pixel based analysis. Also some comments concerning the retrieval of information on the vertical properties of a single building are reported.

  16. Detecting Rock Glacier Dynamics in Southern Carpathians Mountains Using High-Resolution Optical and Multi-Temporal SAR Satellite Imagery .....

    Science.gov (United States)

    Necsoiu, M.; Onaca, A.

    2015-12-01

    This research provided the first documented assessment of the dynamics of rock glaciers in Southern Carpathian Mountains over almost half a century (1968-2014). The dynamics of four representative rock glaciers were assessed using complementary satellite-based optical and radar remote sensing techniques. We investigated the dynamics of the area using co-rectification of paired optical satellite datasets acquired by SPOT5, WV-1, Pléiades, and Corona to estimate short term (7 years) and longer term changes (44 years). Accurately rectifying and co-registering Corona KH-4B imagery allowed us to expand the time horizon over which changes in this alpine environment could be analyzed. The displacements revealed by this analysis correlate with variations in local slope of the rock glaciers, and presence or absence of permafrost. For radar analysis, nine ascending ALOS-1 PALSAR images were used based clear sky and absence of snow groundcover (i.e. June-October). Although decorrelation limits the ability to perform quantitative InSAR analyses, loss of coherence was useful in detecting subtle changes in active rock glacier environments, as well as other mass movements including rock falls, rock avalanches, debris flows, creep of permafrost, and solifluction. Small Baseline Subset (SBAS) InSAR analysis successfully quantified rates of change for unstable areas. The results of this investigation, although based on limited archived imagery, demonstrate that correlation analysis, coherence analysis, and multitemporal InSAR techniques can yield useful information for detecting creeping permafrost in a complex mountain environment, such as Retezat Mountains. Our analyses showed that rock glaciers in the Southern Carpathian Mountains are experiencing very slow annual movement of only a few cm per year. Results of the remote sensing analyses are consistent with field observations of permafrost occurrence at these sites (for more, please see Abstract ID# 68413). The combined optical

  17. Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching

    Science.gov (United States)

    Hu, Jun; Li, Zhi-Wei; Ding, Xiao-Li; Zhu, Jian-Jun

    2008-01-01

    The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS) direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D) co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction), with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground). Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more advantageous than the DInSAR

  18. Polarimetric SAR Image Supervised Classification Method Integrating Eigenvalues

    Directory of Open Access Journals (Sweden)

    Xing Yanxiao

    2016-04-01

    Full Text Available Since classification methods based on H/α space have the drawback of yielding poor classification results for terrains with similar scattering features, in this study, we propose a polarimetric Synthetic Aperture Radar (SAR image classification method based on eigenvalues. First, we extract eigenvalues and fit their distribution with an adaptive Gaussian mixture model. Then, using the naive Bayesian classifier, we obtain preliminary classification results. The distribution of eigenvalues in two kinds of terrains may be similar, leading to incorrect classification in the preliminary step. So, we calculate the similarity of every terrain pair, and add them to the similarity table if their similarity is greater than a given threshold. We then apply the Wishart distance-based KNN classifier to these similar pairs to obtain further classification results. We used the proposed method on both airborne and spaceborne SAR datasets, and the results show that our method can overcome the shortcoming of the H/α-based unsupervised classification method for eigenvalues usage, and produces comparable results with the Support Vector Machine (SVM-based classification method.

  19. MIMO-OFDM signal optimization for SAR imaging radar

    Science.gov (United States)

    Baudais, J.-Y.; Méric, S.; Riché, V.; Pottier, É.

    2016-12-01

    This paper investigates the optimization of the coded orthogonal frequency division multiplexing (OFDM) transmitted signal in a synthetic aperture radar (SAR) context. We propose to design OFDM signals to achieve range ambiguity mitigation. Indeed, range ambiguities are well known to be a limitation for SAR systems which operates with pulsed transmitted signal. The ambiguous reflected signal corresponding to one pulse is then detected when the radar has already transmitted the next pulse. In this paper, we demonstrate that the range ambiguity mitigation is possible by using orthogonal transmitted wave as OFDM pulses. The coded OFDM signal is optimized through genetic optimization procedures based on radar image quality parameters. Moreover, we propose to design a multiple-input multiple-output (MIMO) configuration to enhance the noise robustness of a radar system and this configuration is mainly efficient in the case of using orthogonal waves as OFDM pulses. The results we obtain show that OFDM signals outperform conventional radar chirps for range ambiguity suppression and for robustness enhancement in 2 ×2 MIMO configuration.

  20. Information compression and speckle reduction for multifrequency polarimetric SAR images based on kernel PCA

    Institute of Scientific and Technical Information of China (English)

    Li Ying; Lei Xiaogang; Bai Bendu; Zhang Yanning

    2008-01-01

    Multifrequency polarimetric SAR imagery provides a very convenient approach for signal processing and acquisition of radar image. However, the amount of information is scattered in several images, and redundancies exist between different bands and polarizations. Similar to signal-polarimetric SAR image, multifrequency polarimetric SAR image is corrupted with speckle noise at the same time. A method of information compression and speckle reduction for multifrequency polarimetric SAR imagery is presented based on kernel principal component analysis (KPCA). KPCA is a nonlinear generalization of the linear principal component analysis using the kernel trick. The NASA/JPL polarimetric SAR imagery of P, L, and C bands quadpolarizations is used for illustration. The experimental results show that KPCA has better capability in information compression and speckle reduction as compared with linear PCA.

  1. THE FAST FIXED-POINT ALGORITHM FOR SPECKLE REDUCTION OF POLARIMETRIC SAR IMAGE

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Chen Xiaoning; Pi Yiming; Hou Yinming

    2005-01-01

    In this letter, a simple and efficient method of image speckle reduction for polarimetric SAR is put forward. It is based on the fast fixed-point ICA (Independent Component Analysis) algorithm of orthogonal and symmetric matrix. Simulation experiment is carried out to separate speckle noise from the polarimetric SAR images, and it indicates that this algorithm has high convergency speed and stability, the image speckle noise is reduced effectively and the speckle index is low, and the image quality is improved obviously.

  2. COMPARISON OF FILTERS DEDICATED TO SPECKLE SUPPRESSION IN SAR IMAGES

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    Full Text Available This paper presents the results of research on the effectiveness of different filtering methods dedicated to speckle suppression in SAR images. The tests were performed on RadarSat-2 images and on an artificial image treated with simulated speckle noise. The research analysed the performance of particular filters related to the effectiveness of speckle suppression and to the ability to preserve image details and edges. Speckle is a phenomenon inherent to radar images – a deterministic noise connected with land cover type, but also causing significant changes in digital numbers of pixels. As a result, it may affect interpretation, classification and other processes concerning radar images. Speckle, resembling “salt and pepper” noise, has the form of a set of relatively small groups of pixels of values markedly different from values of other pixels representing the same type of land cover. Suppression of this noise may also cause suppression of small image details, therefore the ability to preserve the important parts of an image, was analysed as well. In the present study, selected filters were tested, and methods dedicated particularly to speckle noise suppression: Frost, Gamma-MAP, Lee, Lee-Sigma, Local Region, general filtering methods which might be effective in this respect: Mean, Median, in addition to morphological filters (alternate sequential filters with multiple structuring element and by reconstruction. The analysis presented in this paper compared the effectiveness of different filtering methods. It proved that some of the dedicated radar filters are efficient tools for speckle suppression, but also demonstrated a significant efficiency of the morphological approach, especially its ability to preserve image details.

  3. Coastal Monitoring Using L-band Synthetic Aperture Radar (SAR) Image Data - Some Case Studies in Asian Delta Areas

    Science.gov (United States)

    Tanaka, A.

    2014-12-01

    Coastal geomorphology is highly variable as it is affected by sea-level changes and other naturally- and human-induced fluctuations. To effectively assess and monitor geomorphological changes in various time scales is thus critical for coastal management. Asian mega deltas are vulnerable to a sea-level rise due to its low-lying delta plain, and are dynamic region given a large amount of sediment supply. However, limited data availability and accessibility in the deltas have prevented establishment of systematic coastal monitoring. A variety of remote sensing systems can be used to monitor geomorphological changes in coastal areas as it has wide spatial coverage and high temporal repeatability. Especially, analysis using SAR (Synthetic Aperture Radar) data not affected by the cloud conditions offer potential for monitoring in the monsoon Asia region. We will present some case studies of Asian coastal regions using L-band SAR data, ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band SAR) and JERS-1 (Japanese Earth Resource Satellite-1) SAR data. One example is that time-series of radar amplitude images can be used to delineate changes quantitatively of the areal extent of river-mouth bars in distributaries of the Mekong River delta. It shows that the estimated areas of river mouthbars gradually increase on an annual time scale, and seasonal variations of areas were also recognized. Another example is that differential SAR interferometry is applied to the coast of the Yellow River delta in China. It shows very high subsidence rates, likely due to groundwater pumping. A further example is that we apply a SAR interferometry time series analysis to monitor ground deformations in the lower Chao Phraya delta plain, Thailand. A single reference time series interferogram from the stacking of unwrapped phases were applied. The subsidence and uplift pattern observed using the SAR interferometry time series analysis highlights the spatial complexity

  4. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    OpenAIRE

    Lu Ping-ping; Du Kang-ning; Yu Wei-dong; Wang Yu; Deng Yun-kai

    2014-01-01

    Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extracti...

  5. PERFORMANCE EVALUATION OF SEVERAL FUSION APPROACHES FOR CCD/SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Several image fusion approaches for CCD/SAR images are studied and the performance evaluation of these fusion approaches is completed in this paper. Firstly, the preprocessing of CCD/SAR images before fusion is fulfilled. Then, the image fusion methods including linear superposition, nonlinear operator method and multiresolution methods, of which the multiresolution methods include Laplacian pyramid, ratio pyramid, contrast pyramid, gradient pyramid, morphological pyramid and discrete wavelet transform, are adopted to fuse two types of images. Lastly, the four performance measures, standard deviation, entropy, cross entropy and spatial frequency, are calculated to compare the fusion results by different fusion approaches in this paper. Experimental results show that contrast pyramid, morphology pyramid and discrete wavelet transformation in multiresolution approaches are more suitable for CCD/SAR image fusion than other ones proposed in this paper and the objective performance evaluation of CCD/SAR image fusion approaches are effective.

  6. Decorrelating Clutter Statistics for Long Integration Time SAR Imaging

    Science.gov (United States)

    Leanza, Antonio; Monti Guarnieri, Andrea; Recchia, Andrea; Broquetas Ibars, Antoni; Ruiz Rodon, Josep

    2015-05-01

    It is presented an experiment aimed to assess and eventually complement the Billingsley Internal Clutter Motion (ICM) model for long integration time SAR imaging. Exploiting a real-aperture rotating antenna Ground-Based RADAR, observations of rural areas in different periods of the year have been performed. The collected data, obtained from two different acquisition modes, have been processed to obtain short-term and long-term clutter de-correlation analysis. The results obtained revealed interesting aspects of the phenomenon. In particular, it can be observed that the process is non-stationary with time, say minutes to hours, and that DC/AC ratio follows a day/night characteristic. Moreover, the results showed values of the AC component decay rate β higher than the foreseen ones in the considered spectral interval, which is quite below the one analyzed in the Billingsley experiment.

  7. Fast Detection of Oil Spills and Ships Using SAR Images

    Directory of Open Access Journals (Sweden)

    Alberto Lupidi

    2017-03-01

    Full Text Available In this paper, we show the capabilities of a new maritime control system based on the processing of COSMO-SkyMed Synthetic Aperture Radar (SAR images. This system aims at fast detection of ships that may be responsible for illegal oil dumping. In particular, a novel detection algorithm based on the joint use of the significance parameter, wavelet correlator and a two-dimensional Constant False Alarm Rate (2D-CFAR is designed. Results show the effectiveness of such algorithms, which can be used by the maritime authorities to have a faster although still reliable response. The proposed algorithm, together with the short revisit time of the COSMO-SkyMed constellation, can help with tracking the scenario evolution from one acquisition to the next.

  8. Satellite-based RAR performance simulation for measuring directional ocean wave spectrum based on SAR inversion spectrum

    Institute of Scientific and Technical Information of China (English)

    REN Lin; MAO Zhihua; HUANG Haiqing; GONG Fang

    2010-01-01

    Some missions have been carried out to measure wave directional spectrum by synthetic aperture radar (SAR) and airborne real aperture radar (RAR) at a low incidence. Both them have their own advantages and limitations. Scientists hope that SAR and satellite-based RAR can complement each other for the research on wave properties in the future. For this study, the authors aim to simulate the satellite-based RAR system to validate performance for measuring the directional wave spectrum. The principal measurements are introduced and the simulation methods based on the one developed by Hauser are adopted and slightly modified. To enhance the authenticity of input spectrum and the wave spectrum measuring consistency for SAR and satellite-based RAR, the wave height spectrum inversed from Envisat ASAR data by cross spectrum technology is used as the input spectrum of the simulation system. In the process of simulation, the sea surface, backscattering signal, modulation spectrum and the estimated wave height spectrum are simulated in each look direction. Directional wave spectrum are measured based on the simulated observations from 0° to 360~. From the estimated wave spectrum, it has an 180° ambiguity like SAR, but it has no special high wave number cut off in all the direction. Finally, the estimated spectrum is compared with the input one in terms of the dominant wave wavelength, direction and SWH and the results are promising. The simulation shows that satellite-based RAR should be capable of measuring the directional wave properties. Moreover, it indicates satellite-based RAR basically can measure waves that SAR can measure.

  9. Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection

    Directory of Open Access Journals (Sweden)

    Antonino Maltese

    2013-03-01

    Full Text Available Monitoring spatial and temporal variability of vegetation is important to manage land and water resources, with significant impact on the sustainability of modern agriculture. Cloud cover noticeably reduces the temporal resolution of retrievals based on optical data. COSMO-SkyMed (the new Italian Synthetic Aperture RADAR-SAR opened new opportunities to develop agro-hydrological applications. Indeed, it represents a valuable source of data for operational use, due to the high spatial and temporal resolutions. Although X-band is not the most suitable to model agricultural and hydrological processes, an assessment of vegetation development can be achieved combing optical vegetation indices (VIs and SAR backscattering data. In this paper, a correlation analysis has been performed between the crossed horizontal-vertical (HV backscattering (s°HV and optical VIs (VIopt on several plots. The correlation analysis was based on incidence angle, spatial resolution and polarization mode. Results have shown that temporal changes of s°HV (Δs°HV acquired with high angles (off nadir angle; θ > 40° best correlates with variations of VIopt (ΔVI. The correlation between ΔVI and Δs°HV has been shown to be temporally robust. Based on this experimental evidence, a model to infer a VI from s° (VISAR at the time, ti + 1, once known, the VIopt at a reference time, ti, and Δs°HV between times, ti + 1 and ti, was implemented and verified. This approach has led to the development and validation of an algorithm for coupling a VIopt derived from DEIMOS-1 images and s°HV. The study was carried out over the Sele plain (Campania, Italy, which is mainly characterized by herbaceous crops. In situ measurements included leaf area index (LAI, which were collected weekly between August and September 2011 in 25 sites, simultaneously to COSMO-SkyMed (CSK and DEIMOS-1 imaging. Results confirm that VISAR obtained using the combined model is able to increase the feasibility

  10. SAR Imaging Technology Makes Major Advances in China over the Past 25 Years

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    @@ On September 17, 1979, scientists from the CAS Institute of Electronics succeeded in obtaining their first microwave remote sensing images from a prototype airborne synthetic aperture radar (SAR) system. Over the past 25 years, Chinese scientists have won many R&D results and made remarkable progress in developing SAR and its ground receiving systems.

  11. An imaging algorithm based on keystone transform for one-stationary bistatic SAR of spotlight mode

    Science.gov (United States)

    Qiu, Xiaolan; Behner, Florian; Reuter, Simon; Nies, Holger; Loffeld, Otmar; Huang, Lijia; Hu, Donghui; Ding, Chibiao

    2012-12-01

    This article proposes an imaging algorithm based on Keystone Transform for bistatic SAR with a stationary receiver. It can efficiently be applied to high-resolution spotlight mode, and can directly be process the bistatic SAR data which have been ranged compressed by the synchronization reference pulses. Both simulation and experimental results validate the good performance of this algorithm.

  12. Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2017-02-01

    Full Text Available By acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies with image parameters, such as aspect and incidence angle. To investigate vehicle detectability in SAR images for traffic monitoring applications, images of four common types of vehicles in China were acquired using the fully polarimetric (FP SAR of Radarsat-2 in our experiments. Methods for measuring a vehicle’s aspect angle and backscatter intensity are introduced. The experimental FP SAR images are used to analyze the detectability, which is affected by factors such as vehicle size, vehicle shape, and aspect angle. Moreover, a new metric to improve vehicle detectability in FP SAR images is proposed and compared with the well-known intensity metric. The experimental results show that shape is a crucial factor in affecting the backscatter intensity of vehicles, which also oscillates with varying aspect angle. If the size of a vehicle is smaller than the SAR image resolution, using the intensity metric would result in low detectability. However, it could be improved in an FP SAR image by using the proposed metric. Compared with the intensity metric, the overall detectability is improved from 72% to 90% in our experiments. Therefore, this study indicates that FP SAR images have the ability to detect stationary vehicles on the road and are meaningful for traffic monitoring.

  13. 25 years of satellite InSAR monitoring of ground instability and coastal geohazards in the archaeological site of Capo Colonna, Italy

    Science.gov (United States)

    Cigna, F.; Confuorto, P.; Novellino, A.; Tapete, D.; Di Martire, D.; Ramondini, M.; Calcaterra, D.; Plank, S.; Ietto, F.; Brigante, A.; Sowter, A.

    2016-10-01

    For centuries the promontory of Capo Colonna in Calabria region, southern Italy, experienced land subsidence and coastline retreat to an extent that the archaeological ruins of the ancient Greek sanctuary are currently under threat of cliff failure, toppling and irreversible loss. Gas extraction in nearby wells is a further anthropogenic element to account for at the regional scale. Exploiting an unprecedented satellite Synthetic Aperture Radar (SAR) time series including ERS-1/2, ENVISAT, TerraSAR-X, COSMO-SkyMed and Sentinel-1A data stacks acquired between 1992 and 2016, this paper presents the first and most complete Interferometric SAR (InSAR) baseline assessment of land subsidence and coastal processes affecting Capo Colonna. We analyse the regional displacement trends, the correlation between vertical displacements with gas extraction volumes, the impact on stability of the archaeological heritage, and the coastal geohazard susceptibility. In the last 25 years, the land has subsided uninterruptedly, with highest annual line-of-sight deformation rates ranging between -15 and -20 mm/year in 2011-2014. The installation of 40 pairs of corner reflectors along the northern coastline and within the archaeological park resulted in an improved imaging capability and higher density of measurement points. This proved to be beneficial for the ground stability assessment of recent archaeological excavations, in an area where field surveying in November 2015 highlighted new events of cliff failure. The conceptual model developed suggests that combining InSAR results, geomorphological assessments and inventorying of wave-storms will contribute to unveil the complexity of coastal geohazards in Capo Colonna.

  14. SAR Images Unsupervised Change Detection Based on Combination of Texture Feature Vector with Maximum Entropy Principle

    Directory of Open Access Journals (Sweden)

    ZHUANG Huifu

    2016-03-01

    Full Text Available Generally, spatial-contextual information would be used in change detection because there is significant speckle noise in synthetic aperture radar(SAR images. In this paper, using the rich texture information of SAR images, an unsupervised change detection approach to high-resolution SAR images based on texture feature vector and maximum entropy principle is proposed. The difference image is generated by using the 32-dimensional texture feature vector of gray-level co-occurrence matrix(GLCM. And the automatic threshold is obtained by maximum entropy principle. In this method, the appropriate window size to change detection is 11×11 according to the regression analysis of window size and precision index. The experimental results show that the proposed approach is better could both reduce the influence of speckle noise and improve the detection accuracy of high-resolution SAR image effectively; and it is better than Markov random field.

  15. SAR imaging simulation for an inhomogeneous undulated lunar surface based on triangulated irregular network

    Institute of Scientific and Technical Information of China (English)

    FA WenZhe; XU Feng; JIN YaQiu

    2009-01-01

    Based on the statistics of the lunar cratered terrain, e.g., population, dimension and shape of craters, the terrain feature of cratered lunar surface is numerically generated. According to the Inhomogeneous distribution of the lunar surface slope, the triangulated irregular network (TIN) is employed to make the digital elevation of lunar surface model. The Kirchhoff approximation of surface scattering is then applied to simulation of lunar surface scattering. The synthetic aperture radar (SAR) image for compre-hensive cratered lunar surface is numerically generated using back projection (BP) algorithm of SAR Imaging. Making use of the digital elevation and Clementlne UVVIS data at Apollo 15 landing site as the ground truth, an SAR Image at Apollo 15 landing site Is simulated. The image simulation is verified using real SAR image and echoes statistics.

  16. Stereo analysis of high-resolution SAR images for building height estimation in cases of orthogonal aspect directions

    Science.gov (United States)

    Soergel, Uwe; Michaelsen, Eckart; Thiele, Antje; Cadario, Erich; Thoennessen, Ulrich

    SAR stereo image analysis for 3D information extraction is mostly carried out based on imagery taken under same-side or opposite-side viewing conditions. For urban scenes in practice stereo is up to now usually restricted to the first configuration, because increasing image dissimilarity connected with rising illumination direction differences leads to a lack of suitable features for matching, especially in the case of low or medium resolution data. However, due to two developments SAR stereo from arbitrary viewing conditions becomes an interesting option for urban information extraction. The first one is the availability of airborne sensor systems, which are capable of more flexible data acquisition in comparison to satellite sensors. This flexibility enables multi-aspect analysis of objects in built-up areas for various kinds of purpose, such as building recognition, road network extraction, or traffic monitoring. The second development is the significant improvement of the geometric resolution providing a high level of detail especially of roof features, which can be observed from a wide span of viewpoints. In this paper, high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their height from the different layover effects in views taken from orthogonal aspect angles. High level object matching is proposed that relies on symbolic data, representing suitable features of urban objects. Here, a knowledge-based approach is applied, which is realized by a production system that codes a set of suitable principles of perceptual grouping in its production rules. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows of point targets, rectangular structures or symmetries. The stereo analysis is then accomplished by means of productions that combine and match these 2D image objects and infer their height by 3D clustering. The approach

  17. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

    Science.gov (United States)

    Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

    2016-04-07

    With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  18. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

    Directory of Open Access Journals (Sweden)

    Fan Zhang

    2016-04-01

    Full Text Available With the development of synthetic aperture radar (SAR technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO. However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  19. Visual analytics for semantic queries of TerraSAR-X image content

    Science.gov (United States)

    Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

    2015-10-01

    With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain

  20. Fast SAR Image Change Detection Using Bayesian Approach Based Difference Image and Modified Statistical Region Merging

    Directory of Open Access Journals (Sweden)

    Han Zhang

    2014-01-01

    Full Text Available A novel fast SAR image change detection method is presented in this paper. Based on a Bayesian approach, the prior information that speckles follow the Nakagami distribution is incorporated into the difference image (DI generation process. The new DI performs much better than the familiar log ratio (LR DI as well as the cumulant based Kullback-Leibler divergence (CKLD DI. The statistical region merging (SRM approach is first introduced to change detection context. A new clustering procedure with the region variance as the statistical inference variable is exhibited to tailor SAR image change detection purposes, with only two classes in the final map, the unchanged and changed classes. The most prominent advantages of the proposed modified SRM (MSRM method are the ability to cope with noise corruption and the quick implementation. Experimental results show that the proposed method is superior in both the change detection accuracy and the operation efficiency.

  1. Structural High-resolution Satellite Image Indexing

    OpenAIRE

    Xia, Gui-Song; YANG, WEN; Delon, Julie; Gousseau, Yann; Sun, Hong; Maître, Henri

    2010-01-01

    International audience; Satellite images with high spatial resolution raise many challenging issues in image understanding and pattern recognition. First, they allow measurement of small objects maybe up to 0.5 m, and both texture and geometrical structures emerge simultaneously. Second, objects in the same type of scenes might appear at different scales and orientations. Consequently, image indexing methods should combine the structure and texture information of images and comply with some i...

  2. Geodetic Imaging of the Coseismic and Postseismic deformation from the 2015 Mw 7.8 Gorkha Earthquake and Mw 7.3 Aftershock in Nepal with SAR and GPS

    Science.gov (United States)

    Fielding, E. J.; Liang, C.; Agram, P. S.; Sangha, S. S.; Huang, M. H.; Samsonov, S. V.; Owen, S. E.; Moore, A. W.; Rodriguez-Gonzalez, F.; Minchew, B. M.

    2015-12-01

    The 25th of April 2015 Mw 7.8 Gorkha Earthquake in Nepal affected a large area of central Nepal and adjacent parts of India and Tibet. It was followed by a number of large aftershocks, with the largest so far an Mw 7.3 aftershock on the 12th of May 2015. We integrate geodetic measurements from Global Positioning System (GPS) data and synthetic aperture radar (SAR) satellite images to image the three-dimensional vector field of coseismic surface deformation for these two large events. We analyze SAR data from the Copernicus Sentinel-1A satellite operated by the European Space Agency; the RADARSAT-2 satellite operated by MacDonald, Dettwiler and Associates (MDA); and the Advanced Land Observation Satellite-2 (ALOS-2) satellite operated by the Japanese Aerospace Exploration Agency. We combine less precise analysis of large scale displacements from the SAR images of the three satellites by pixel offset tracking or sub-pixel correlation, including the along-track component of surface motion, with the more precise SAR interferometry (InSAR) measurements in the radar line-of-sight direction to estimate all three components of the surface displacement for the mainshock and large aftershock. A large area of central Nepal was pushed southward, due to thrust slip on the Main Himalayan Thrust (MHT) at depth extending about 170 km along-strike. The InSAR measurements show that there was no detectable slip on the shallower part of the MHT up-dip from the large coseismic slip or on other thrust faults in the Himalayas, except for one area of very shallow triggered slip of up to 5 cm on a thrust to the north of the Himalayan Frontal Thrust, during the two event. We also image postseismic deformation after these earthquakes with ongoing continuous GPS measurements and InSAR analysis of the SAR satellite data. Initial analysis of the GPS measurements indicates the most likely process in the first months is afterslip down-dip from the main coseismic slip. Large atmospheric effects in

  3. Airborne SAR Real-time Imaging Algorithm Design and Implementation with CUDA on NVIDIA GPU

    Directory of Open Access Journals (Sweden)

    Meng Da-di

    2013-12-01

    Full Text Available Synthetic Aperture Radar (SAR image processing requires huge computation amount. Traditionally, this task runs on the workstation or server based on Central Processing Unit (CPU and is rather time-consuming, hence real-time processing of SAR data is impossible. Based on Compute Unified Device Architecture (CUDA technology, a new plan of SAR imaging algorithm operated on NVIDIA Graphic Processing Unit (GPU is proposed. The new proposal makes it possible that the data processing procedure and CPU/GPU data exchanging execute concurrently, especially when SAR data size exceeds total GPU global memory size. Multi-GPU is suitably supported by the new proposal and all of computational resources are fully exploited. It is shown by experiment on NVIDIA K20C and INTEL E5645 that the proposed solution accelerates SAR data processing by tens of times. Consequently, the GPU based SAR processing system with the proposed solution embedded is much more power saving and portable, which makes it qualified to be a real-time SAR data processing system. Experiment shows that SAR data of 36 Mega points can be processed in real-time per second by K20C with the new solution equipped.

  4. Segmentation-Based PolSAR Image Classification Using Visual Features: RHLBP and Color Features

    Directory of Open Access Journals (Sweden)

    Jian Cheng

    2015-05-01

    Full Text Available A segmentation-based fully-polarimetric synthetic aperture radar (PolSAR image classification method that incorporates texture features and color features is designed and implemented. This method is based on the framework that conjunctively uses statistical region merging (SRM for segmentation and support vector machine (SVM for classification. In the segmentation step, we propose an improved local binary pattern (LBP operator named the regional homogeneity local binary pattern (RHLBP to guarantee the regional homogeneity in PolSAR images. In the classification step, the color features extracted from false color images are applied to improve the classification accuracy. The RHLBP operator and color features can provide discriminative information to separate those pixels and regions with similar polarimetric features, which are from different classes. Extensive experimental comparison results with conventional methods on L-band PolSAR data demonstrate the effectiveness of our proposed method for PolSAR image classification.

  5. Ship Detection in SAR Image Based on the Alpha-stable Distribution

    Directory of Open Access Journals (Sweden)

    Xiaofeng Li

    2008-08-01

    Full Text Available This paper describes an improved Constant False Alarm Rate (CFAR ship detection algorithm in spaceborne synthetic aperture radar (SAR image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution.

  6. Satellite imager calibration and validation

    CSIR Research Space (South Africa)

    Vhengani, L

    2010-10-01

    Full Text Available The success or failure of any earth observation mission depends on the quality of its data. Data quality is assessed by determining the radiometric, spatial, spectral and geometric fidelity of the satellite sensor. The process is termed calval...

  7. A Novel Ship Wake Detection Method of SAR Images Based on Frequency Domain

    Institute of Scientific and Technical Information of China (English)

    Liu Hao; Zhu Minhui

    2003-01-01

    Moving ships produce a set of waves of "V' pattern on the ocean. These waves can often be seen by Synthetic Aperture Radar (SAR). The detection of these wakes can provide important information for surveillance of shipping, such as ship traveling direction and speed. A novel approach to the detection of ship wakes in SAR images based on frequency domain is provided in this letter. Compared with traditional Radon-based approaches, computation is reduced by 20%-40% without losing nearly any of detection performance. The testing results using real data and simulation of synthetic SAR images test the algorithm's feasibility and robustness.

  8. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...

  9. REALIZATION OF QUICK-LOOK IMAGING FOR SPACEBORNE SAR BASED ON PARALLEL PROCESSING

    Institute of Scientific and Technical Information of China (English)

    Tang Zhi; Zhou Yinqing; Li Jingwen

    2004-01-01

    Large range cell migration is a severe challenge to imaging algorithm for spaceborne SAR. Based on design of Finite Impulse Response (FIR) filter and Range Doppler (RD) algorithm,a realization of quick-look imaging for large range cell migration is proposed. It realized quicklook imaging of 8 times reduced resolution with parallel processing on memory shared 8 CPU SGI server. According to simulation experiment, this quick-look imaging algorithm with parallel processing can image 16384× 16384 SAR raw data within 6 seconds. It reaches the requirement of real-time imaging.

  10. Automatic compensation of antenna beam roll-off in SAR images.

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin Walter

    2006-04-01

    The effects of a non-uniform antenna beam are sometimes visible in Synthetic Aperture Radar (SAR) images. This might be due to near-range operation, wide scenes, or inadequate antenna pointing accuracy. The effects can be mitigated in the SAR image by fitting very a simple model to the illumination profile and compensating the pixel brightness accordingly, in an automated fashion. This is accomplished without a detailed antenna pattern calibration, and allows for drift in the antenna beam alignments.

  11. STUDY ON THE TECHNIQUE TO DETECT TEXTURE FEATURES IN SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Ding Dongtao; Hou Yinming

    2004-01-01

    This letter studies on the detection of texture features in Synthetic Aperture Radar (SAR) images. Through analyzing the feature detection method proposed by Lopes, an improved texture detection method is proposed, which can not only detect the edge and lines but also avoid stretching edge and suppressing lines of the former algorithm. Experimental results with both simulated and real SAR images verify the advantage and practicability of the improved method.

  12. Directional Filter for SAR Images Based on Nonsubsampled Contourlet Transform and Immune Clonal Selection

    Institute of Scientific and Technical Information of China (English)

    Xiao-Hui Yang; Li-Cheng Jiao; Deng-Feng Li

    2009-01-01

    A directional filter algorithm for intensity synthetic aperture radar (SAR) image based on nonsubsampled contourlet transform (NSCT) and immune clonal selection (ICS) is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.

  13. Enhancement of SAR images using fuzzy shrinkage technique in curvelet domain

    Indian Academy of Sciences (India)

    SHIVAKUMARA SWAMY PURANIK MATH; VANI KALIYAPERUMAL

    2017-09-01

    The synthetic aperture radar (SAR) images are mainly affected by speckle noise. Speckle degrades the features in the image and reduces the ability of a human observer to resolve fine detail, hence despeckling is very much required for SAR images. This paper presents speckle noise reduction in SAR images using a combination of curvelet and fuzzy logic technique to restore speckle-affected images. This method overcomes the limitation of discontinuity in hard threshold and permanent deviation in soft threshold. First, it decomposes noise image into different frequency scales using curvelet transform, and then applies the fuzzy shrinking technique to high-frequency coefficients to restore noise-contaminated coefficients. The proposed method does not use threshold approach only by proper selection of shrinking parameter the speckle in SAR image is suppressed. The experiment is carried out on different resolutions of RISAT-1 SAR images, and results are compared with the existing filtering algorithms in terms of noise mean variance (NMV), mean square difference (MSD), equal number of looks (ENL), noise standard deviation (NSD) and speckle suppression index (SSI). A comparison of the results shows that the proposed technique suppresses noise significantly, preserves the details of the image and improves the visual quality of the image

  14. A Method for Sea Surface Wind Field Retrieval from SAR Image Mode Data

    Institute of Scientific and Technical Information of China (English)

    SHAO Weizeng; SUN Jian; GUAN Changlong; SUN Zhanfeng

    2014-01-01

    To retrieve wind field from SAR images, the development for surface wind field retrieval from SAR images based on the improvement of new inversion model is present. Geophysical Model Functions (GMFs) have been widely applied for wind field retrieval from SAR images. Among them CMOD4 has a good performance under low and moderate wind conditions. Although CMOD5 is developed recently with a more fundamental basis, it has ambiguity of wind speed and a shape gradient of normalized radar cross section under low wind speed condition. This study proposes a method of wind field retrieval from SAR image by com-bining CMOD5 and CMOD4 Five VV-polarisation RADARSAT2 SAR images are implemented for validation and the retrieval re-sults by a combination method (CMOD5 and CMOD4) together with CMOD4 GMF are compared with QuikSCAT wind data. The root-mean-square error (RMSE) of wind speed is 0.75 m s-1 with correlation coefficient 0.84 using the combination method and the RMSE of wind speed is 1.01 m s-1 with correlation coefficient 0.72 using CMOD4 GMF alone for those cases. The proposed method can be applied to SAR image for avoiding the internal defect in CMOD5 under low wind speed condition.

  15. Pixel Classification of SAR ice images using ANFIS-PSO Classifier

    Directory of Open Access Journals (Sweden)

    G. Vasumathi

    2016-12-01

    Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

  16. Retrieval of Both Soil Moisture and Texture Using one configuration TerraSAR-X radar Images

    Science.gov (United States)

    Zribi, M., Sr.; Gorrab, A.; Baghdadi, N.; Lili-Chabaane, Z.

    2015-12-01

    The aim of this study is to propose a methodology combing multi-temporal X-band SAR images (TerraSAR-X) with continuous ground thetaprobe measurements, for the retrieval of surface soil moisture and texture at a high spatial resolution. Our analysis is based on seven radar images acquired at a 36° incidence angle in the HH polarization, over a semi-arid site in Tunisia (North Africa). All ground measurements of surface soil parameters were carried out over several bare soil reference fields located at the Kairouan site. Between November 2013 and January 2014 (three months), ground campaigns were carried out at the same time as the seven satellite acquisitions. The soil moisture estimations are based on an empirical change detection approach using TerraSAR-X data and ground auxiliary thetaprobe network measurements. Two assumptions were tested: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. For the two considered approaches, the soil moisture estimations were validated using ground measurements acquired over fifteen test fields, under different moisture conditions. These comparisons lead to a volumetric moisture RMSE equal to 3.8% and 3.3%, and a bias equal to 0.5% and 0.3%, respectively. By considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved. For clay and sand, we retrieve an rms error equal to 10.8% (equivalent to 108 g/kg) and 18.6% (equivalent to 186 g/kg), respectively. Maps of soil moisture, clay

  17. Progress on the calibration of channel geometry and friction parameters of the LISFLOOD-FP hydraulic model using time series of SAR flood images

    Science.gov (United States)

    Wood, M.; Neal, J. C.; Hostache, R.; Corato, G.; Bates, P. D.; Chini, M.; Giustarini, L.; Matgen, P.; Wagener, T.

    2014-12-01

    The objective of this work is to calibrate channel depth and roughness parameters of the LISFLOOD-FP Sub-Grid 2D hydraulic model using SAR image-derived flood extent maps. The aim is to reduce uncertainty in flood model predictions for those rivers where channel geometry is unknown and/or cannot be easily measured. In particular we consider the effectiveness of using real SAR data for calibration and whether the number and timings of SAR acquisitions is of benefit to the final result. Terrain data are processed from 2m LiDAR images and inflows to the model are taken from gauged data. As a test case we applied the method to the River Severn between Worcester and Tewkesbury. We firstly applied the automatic flood mapping algorithm of Giustarini[1] et al. (2013) to ENVISAT ASAR (wide swath mode) flood images; generating a series of flood maps. We then created an ensemble of flood extent maps with the hydraulic model (each model representing a unique parameter set). Where there is a favourable comparison between the modelled flood map and the SAR obtained flood map we may suggest an optimal parameter set. Applying the method to a sequence of SAR acquisitions provides insight into the advantages, disadvantages and limitations of using series of acquired images. To complete the investigation we simultaneously explore parameter 'identifiabilty' within a sequence of available satellite observations by adopting the DYNIA method proposed by Wagener[2] et al. (2003). We show where we might most easily detect the depth and roughness parameters within the SAR acquisition sequence. [1] Giustarini. 2013. 'A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X'. IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 4. [2] Wagener. 2003. 'Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis'. Hydrol. Process. 17, 455-476.

  18. An improved Otsu method for oil spill detection from SAR images

    Directory of Open Access Journals (Sweden)

    Fangjie Yu

    2017-07-01

    Full Text Available In recent years, oil spill accidents have become increasingly frequent due to the development of marine transportation and massive oil exploitation. At present, satellite remote sensing is the principal method used to monitor oil spills. Extracting the locations and extent of oil spill spots accurately in remote sensing images reaps significant benefits in terms of risk assessment and clean-up work. Nowadays the method of edge detection combined with threshold segmentation (EDCTS to extract oil information is becoming increasingly popular. However, the current method has some limitations in terms of accurately extracting oil spills in synthetic aperture radar (SAR images, where heterogeneous background noise exists. In this study, we propose an adaptive mechanism based on Otsu method, which applies region growing combined with both edge detection and threshold segmentation (RGEDOM to extract oil spills. Remote sensing images from the Bohai Sea on June 11, 2011 and the Gulf of Dalian on July 17, 2010 are utilized to validate the accuracy of our algorithm and the reliability of extraction results. In addition, results according to EDCTS are used as a comparator to further explore validity. The comparison with results according to EDCTS using the same dataset demonstrates that the proposed self-adapting algorithm is more robust and boasts high-accuracy. The accuracy computing by the adaptive algorithm is significantly improved compared with EDCTS and threshold method.

  19. An integrative synchronization and imaging approach for bistatic spaceborne/stratospheric SAR with a fixed receiver

    Science.gov (United States)

    Zhang, Qilei; Chang, Wenge; Li, Xiangyang

    2013-12-01

    Bistatic spaceborne/stratospheric synthetic aperture radar (SAR) with a fixed receiver is a novel hybrid bistatic SAR system, in which a spaceborne SAR serves as the transmitter of opportunity, while a fixed receiver is mounted on a stratospheric platform. This paper presents an integrative synchronization and imaging approach for this particular system. Firstly, a novel synchronization method using the direct-path signal, which can be collected by a dedicated antenna, is proposed and applied. The synchronization error can be completely removed using the proposed method. However, as the cost of synchronization, the characteristic of synchronized echo's range history becomes quite different from that of general bistatic SAR data. To focus this particular synchronized data, its 2-D spectrum is derived under linear approximations and then a frequency-domain imaging algorithm using two-dimensional inverse scaled Fourier transform (2-DISFT) is proposed. At last, the proposed integrative synchronization and imaging algorithm is verified by simulations.

  20. Monitoring river morphological changes using high resolution multitemporal sar images: a case study on orco river, italy

    Science.gov (United States)

    Mitidieri, Francesco; Nicolina Papa, Maria; Ruello, Giuseppe; Amitrano, Donato; Bizzi, Simone; Demarchi, Luca

    2016-04-01

    Improving the knowledge about river processes by applying innovative monitoring techniques is extremely needed to face the challenge of a better river management. In this paper we test the capability of satellite synthetic aperture radar (SAR) images to enrich the monitoring of river geomorphological processes. Multitemporal SAR images provide observations and measurements at high spatial (3 m), and in particular temporal resolution (15 days). This information if properly processed and classified may significantly enrich our ability to monitor the evolution of river morphological phenomena (erosion/deposition, narrowing/widening, riparian vegetation's evolution and interferences with river flow). This is expected to lead to an enhancements in the river management capabilities, in particular as regards the assessment of hydro-morphological river quality, as strongly suggested by European Commission's Water Framework Directive (2000/60/EC). A case study on the Italian River Orco is here presented. The case study has used a set of 100 COSMO-SkyMed stripmap images (from October 2008 to November 2014) from Italian Space Agency. All the data were acquired with medium look angle (almost 30°) and HH polarization, also for increasing the land-water contrast. Calibration, registration and despeckling procedures were applied on the acquired dataset. In particular, the optimal weighting multitemporal De Grandi filter was adopted in order to allow an effective extraction of the water surfaces contour. This method was applied to extract water contours over the entire historical series of SAR datasets available. Thanks to the generated information we were able to monitor the lateral dynamic of the water channels and infer on the evolutions of erosion/deposition phenomena. To this aim, an RGB representation of multitemporal SAR data was implemented. The series of detected river channel morphological changes was then analyzed in the light of the series of discharge measurements in

  1. Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

    Science.gov (United States)

    Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe

    2016-11-01

    For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

  2. Source parameters of the 2009 L'Aquila earthquake,Italy from Envisat and ALOS satellite SAR images%联合Envisat和ALOS卫星影像确定L'Aquila地震震源机制

    Institute of Scientific and Technical Information of China (English)

    温扬茂; 何平; 许才军; 刘洋

    2012-01-01

    On the 6th April 2009, an MW6. 3 earthquake occurred in the region of L'Aqula of Italy, which caused more than 300 people to lose their lives. In this paper, the Envisat and ALOS satellite interferograms with different incidences and wavelengths are used to invert for the source parameters of the fault activated during the earthquake. Firstly, two-pass interferometry technique is used to obtain the coseismic deformation covering the whole epicenter region, then a combination method of quad-tree and uniform sample is employed to down-sample the original observed datasets. Secondly, the rectangle and triangle dislocation models in elastic half-space and an automated fault discretization method are used to derive the geometric and kinematic characteristic of fault combining with GPS surface displacement measurements. The best-fit solution shows that the distributed slip model can explain the data very well. The inversion result indicates that the fault is dominated by normal movement with small right-lateral strike-slip component. The shortest and longest length of the optimal fault patches based on the observing data are 0. 4 km and 6. 3 km, respectively. The fault slip concentrates mainly in the shallow depth between 5 km and 14 km, and the maximum slip is about 1. 07 m. The inverted geodetic moment is 3. 43×1018 N ? M (MW6. 32), which is excellently consistent with the result of seismology.%2009年4月6日意大利L’Aquila地区发生了Mw6.3级地震,该地震造成了300余人的人员死亡.本文联合不同波长、不同入射倾角的升降轨Envisat和ALOS卫星的差分干涉数据对该地震进行震源机制解的反演研究.研究首先对卫星雷达影像进行二通差分干涉处理,获取了覆盖L' Aquila地震震区的完整InSAR同震形变场,然后结合四叉树和均匀采样方法对原始观测数据进行降采样.在此基础上,联合GPS形变观测数据,利用弹性半空间矩形和三角位错模型,以及

  3. Change detection in high resolution SAR images based on multiscale texture features

    Science.gov (United States)

    Wen, Caihuan; Gao, Ziqiang

    2011-12-01

    This paper studied on change detection algorithm of high resolution (HR) Synthetic Aperture Radar (SAR) images based on multi-scale texture features. Firstly, preprocessed multi-temporal Terra-SAR images were decomposed by 2-D dual tree complex wavelet transform (DT-CWT), and multi-scale texture features were extracted from those images. Then, log-ratio operation was utilized to get difference images, and the Bayes minimum error theory was used to extract change information from difference images. Lastly, precision assessment was done. Meanwhile, we compared with the result of method based on texture features extracted from gray-level cooccurrence matrix (GLCM). We had a conclusion that, change detection algorithm based on multi-scale texture features has a great more improvement, which proves an effective method to change detect of high spatial resolution SAR images.

  4. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.;

    2006-01-01

    Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

  5. The chest X-ray image features of patients with severe SARS: a preliminary study

    Institute of Scientific and Technical Information of China (English)

    刘晋新; 唐小平; 江松峰; 陈碧华; 张烈光; 黄德扬; 黄务枝; 史红玲; 尹炽标; 陈金城

    2003-01-01

    Objective To study the chest X-ray image features of patients with severe SARS.Methods Chest X-ray image features in 36 patients with severe SARS were retrospectively analyzed. The image characteristics were compared with those of 224 patients with common SARS. Results The important chest X-ray imaging features of 36 patients with severe SARS included small patch of infiltration (n=27, 75.0%), large patch of infiltration (n=22, 61.1%), large area of lung consolidation (n=10, 27.3%), interstitial lung lesion (n=26, 72.2%), ground-glass shadow (n=28, 77.8%), irregular linear opacity (n=15, 41.7%), diffuse lung lesion (n=12, 33.3%), with single lung involved (n=9, 25.0%), and both lungs involved (n=32, 88.9%). The rates of large patch of infiltration, large area of lung consolidation, ground-glass shadow, diffuse lung lesion and involvement of both lungs in patients with severe SARS were significantly higher than those in patients with common type of SARS (all P<0.01). Out of the 11 severe SARS patients who died, nine had large area of ground-glass shadow with air bronchogram in both lungs before death.Conclusions Large patch of infiltration, large area of consolidation, ground-glass shadow, diffuse lung lesion and involvement of both lungs were the main X-ray image characteristics of patients with severe SARS. Large area of ground-glass shadow with air bronchogram in both lungs indicated a bad prognosis.

  6. A three-component method for timely detection of land cover changes using polarimetric SAR images

    Science.gov (United States)

    Qi, Zhixin; Yeh, Anthony Gar-On; Li, Xia; Zhang, Xiaohu

    2015-09-01

    This study proposes a new three-component method for timely detection of land cover changes using polarimetric synthetic aperture radar (PolSAR) images. The three components are object-oriented image analysis (OOIA), change vector analysis (CVA), and post-classification comparison (PCC). First, two PolSAR images acquired over the same area at different dates are segmented hierarchically to delineate land parcels (image objects). Then, parcel-based CVA is performed with the coherency matrices of the PolSAR data to detect changed parcels. Finally, PCC based on a parcel-based classification algorithm integrating polarimetric decomposition, decision tree algorithms, and support vector machines is used to determine the type of change for the changed parcels. Compared with conventional PCC based on the widely used Wishart supervised classification, the three-component method achieves much higher accuracy for land cover change detection with PolSAR images. The contribution of each component is evaluated by excluding it from the method. The integration of OOIA in the method greatly reduces the false alarms caused by speckle noise in PolSAR images as well as improves the accuracy of PolSAR image classification. CVA contributes to the method by significantly reducing the effect of the classification errors on the change detection. The use of PCC in the method not only identifies different types of land cover change but also reduces the false alarms introduced by the change in the environment. The three-component method is validated in land development detection, which is important to many developing countries that are confronting a growing problem of unauthorized construction land expansion. The results show that the three-component method is effective in detecting land developments with PolSAR images.

  7. SAR imaging method based on coprime sampling and nested sparse sampling

    Institute of Scientific and Technical Information of China (English)

    Hongyin Shi; Baojing Jia

    2015-01-01

    As the signal bandwidth and the number of channels increase, the synthetic aperture radar (SAR) imaging system pro-duces huge amount of data according to the Shannon-Nyquist theorem, causing a huge burden for data transmission. This pa-per concerns the coprime sampling and nested sparse sampling, which are proposed recently but have never been applied to real world for target detection, and proposes a novel way which uti-lizes these new sub-Nyquist sampling structures for SAR sam-pling in azimuth and reconstructs the data of SAR sampling by compressive sensing (CS). Both the simulated and real data are processed to test the algorithm, and the results indicate the way which combines these new undersampling structures and CS is able to achieve the SAR imaging effectively with much less data than regularly ways required. Final y, the influence of a little sam-pling jitter to SAR imaging is analyzed by theoretical analysis and experimental analysis, and then it concludes a little sampling jitter have no effect on image quality of SAR.

  8. Incorporating uncertanity into Markov random field classification with the combine use of optical and SAR images and aduptive fuzzy mean vector

    Science.gov (United States)

    Welikanna, D. R.; Tamura, M.; Susaki, J.

    2014-09-01

    A Markov Random Field (MRF) model accounting for the classification uncertainty using multisource satellite images and an adaptive fuzzy class mean vector is proposed in this study. The work also highlights the initialization of the class values for an MRF based classification for synthetic aperture radar (SAR) images using optical data. The model uses the contextual information from the optical image pixels and the SAR pixel intensity with corresponding fuzzy grade of memberships respectively, in the classification mechanism. Sub pixel class fractions estimated using Singular Value Decomposition (SVD) from the optical image initializes the class arrangement for the MRF process. Pair-site interactions of the pixels are used to model the prior energy from the initial class arrangement. Fuzzy class mean vector from the SAR intensity pixels is calculated using Fuzzy C-means (FCM) partitioning. Conditional probability for each class was determined by a Gamma distribution for the SAR image. Simulated annealing (SA) to minimize the global energy was executed using a logarithmic and power-law combined annealing schedule. Proposed technique was tested using an Advanced Land Observation Satellite (ALOS) phased array type L-band SAR (PALSAR) and Advanced Visible and Near-Infrared Radiometer-2 (AVNIR-2) data set over a disaster effected urban region in Japan. Proposed method and the conventional MRF results were evaluated with neural network (NN) and support vector machine (SVM) based classifications. The results suggest the possible integration of an adaptive fuzzy class mean vector and multisource data is promising for imprecise class discrimination using a MRF based classification.

  9. Error Estimation and Unambiguous Reconstruction for Chinese First Dual-Channel Spaceborne SAR Imaging

    Science.gov (United States)

    Jin, T.; Qiu, X.; Hu, D.; Ding, C.

    2017-09-01

    Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF) process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems.

  10. A SIFT Algorithm for Bistatic SAR Imaging in Spaceborne Constant-offset Configuration (in English

    Directory of Open Access Journals (Sweden)

    Chen Shi-chao

    2013-03-01

    Full Text Available Focusing on the problem of the space-variance of the range cell migration term for bistatic Synthetic Aperture Radar (SAR, a Scaled Inverse Fourier Transform (SIFT based imaging algorithm for constant-offset configuration bistatic SAR data processing is proposed in this article. Range cell migration correction is realized through two times phase multiplies and one time convolution operation. Since the imaging algorithm is based on an exact precise spectrum which is deduced from the Geometry-Based Formula (GBF algorithm, the proposed algorithm can handle the bistatic SAR data which are obtained with a large baseline to ratio. The advantages and effectiveness of the proposed imaging method have been verified by simulated and comparable experiments. Moreover, unlike the other scaling imaging algorithms which are dependent on the frequency modulated characteristics of the signal, the SIFT imaging algorithm is also suitable for phase-coded signal, which has a wider application areas.

  11. AN EVIDENT SIDELOBE CONTROL METHOD BASED ON NSCT FOR SHIP TARGET IN SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    Li Xueying; Yin Dong; Zhang Rong; Wang Kui

    2011-01-01

    Evident sidelobe on faint ship target seriously affects the accuracy of the target segmentation in Synthetic Aperture Radar (SAR) images.To avoid this problem,a novel sidelobe control method based on NonSubsampled Contourlet Transform (NSCT) for ship targets in SAR images is presented in this paper.This method enhances the SAR images in NSCT domain based on target azimuth estimation and then inhibits the sidelobe directionally in NSCT high-pass frequency subbands.Experimental results on RADARSAT-2 images demonstrate that the proposed method can not only reduce the strong sidelobes effectively,but also enhance the intensity of the objects successfully.Therefore,it gives a good segmentation result on the dark ship images with strong sidelobe,and enhances the detection rate on these targets.

  12. Detection and Imaging of Moving Targets with LiMIT SAR Data

    Science.gov (United States)

    2017-03-03

    1 Detection and Imaging of Moving Targets with LiMIT SAR Data Michael Newey, Gerald Benitz, David Barrett MIT Lincoln Laboratory Lexington...sandeep.mishra@baesystems.com Abstract Detecting moving targets in SAR imagery has recently gained a lot of interest as a way to replace optical...moving target detection and classification in adverse (e.g. cloudy) weather conditions. This can be particularly important for small radar antennas

  13. Simultaneous measurements from the Millstone Hill radar and the Active satellite during the SAID/SAR arc event of the March 1990 CEDAR storm

    Directory of Open Access Journals (Sweden)

    M. Förster

    Full Text Available During a nearby passage of the Active satellite above the Millstone Hill radar on 21 March 1990 at local sunset, the satellite and the radar performed simultaneous measurements of upper ionospheric parameters in nearly the same spatial volume. For this purpose the radar carried out a special azimuth-elevation scan to track the satellite. Direct comparisons of radar data and in situ satellite measurements have been carried out quite rarely. In this case, the coincidence of co-ordinated measurements and active ionospheric-magnetospheric processes during an extended storm recovery phase presents a unique occasion resulting in a very valuable data set. The measurements show generally good agreement both during quiet prestorm and storm conditions and the combination of radar and satellite observations gives a more comprehensive picture of the physical processes involved. We find a close relationship between the rapid westward ion drift peak at subauroral latitudes (SAID event and the occurrence of a stable auroral red (SAR arc observed after sunset by an all-sky imager and reported in an earlier study of this event. The SAID electric field is caused by the penetration of energetic ions with energies between about 1 keV and 100 keV into the outer plasmasphere to a latitude equatorward of the extent of the plasmasheet electrons. Charge separation results in the observed polarisation field and the SAID. Unusually high molecular ion densities measured by the satellite at altitudes of 700-870 km at subauroral and auroral latitudes point on strong upward-directed ion acceleration processes and an intense neutral gas upwelling. These structures are collocated with a narrow trough in electron density and an electron temperature peak as observed simultaneously by the radar and the satellite probes.

    Key words. Ionosphere (ionosphere-magnetosphere interactions; plasma temperature and density; Magnetospheric physics (plasmasphere.

  14. Low-Cost Satellite Infrared Imager Study

    Science.gov (United States)

    2007-11-02

    2,297.00 10 MATLAB , Simulink , Symbolic Math Toolbox (2 ea @ £894) £1,788.00 11 MATLAB Image Processing Toolbox (2 ea at £192) £384.00 12 MATLAB ...Figure 1: MWIR and TIR satellite imagery. On the left is a BIRD image of forest fires on the Portuguese/ Spanish border3 and the image on right is...space-borne MWIR and TIR imagers, instrument engineers are continually evaluating advances in the miniaturization of detector technology. One

  15. On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

    Science.gov (United States)

    Medina Revera, Edwin J.; Espinosa, Ramon Vasquez

    1997-01-01

    The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

  16. MULTI-REGION SEGMENTATION OF SAR IMAGE BY A MULTIPHASE LEVEL SET APPROACH

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Cao Zongjie; Pi Yiming

    2008-01-01

    In this letter, a multiphase level set approach unifying region and boundary-based infor- mation for multi-region segmentation of Synthetic Aperture Radar (SAR) image is presented. An energy functional that is applicable for SAR image segmentation is defined. It consists of two terms describing the local statistic characteristics and the gradient characteristics of SAR image respectively. A multiphase level set model that explicitly describes the different regions in one image is proposed. The purpose of such a multiphase model is not only to simplify the way of denoting multi-region by level set but also to guarantee the accuracy of segmentation. According to the presented multiphase model, the curve evolution equations with respect to edge curves are deduced. The multi-region segmentation is implemented by the numeric solution of the partial differential equations. The performance of the approach is verified by both simulation and real SAR images. The experiments show that the proposed algorithm reduces the speckle effect on segmentation and increases the boundary alignment accuracy, thus correctly divides the multi-region SAR image into different homogenous regions.

  17. SAR image change detection algorithm based on stationary wavelet and bi-dimensional intrinsic mode function

    Science.gov (United States)

    Huang, S. Q.; Wang, Z. L.; Xie, T. G.; Li, Z. C.

    2017-09-01

    Speckle noise in synthetic aperture radar (SAR) image is produced by the coherent imaging mechanism, which brings a great impact on the change information acquisition of multi-temporal SAR images. Two-dimensional stationary wavelet transform (SWT) and bi-dimensional empirical mode decomposition (BEMD) are the non-stationary signal processing theory of multi-scale transform. According to their implementation process and SAR image characteristic, this paper proposed a new multi-temporal SAR image change detection method based on the combination of the stationary wavelet transform and the bi-dimensional intrinsic mode function (BIMF) features, called SWT-BIMF algorithm. The contribution of the new algorithm includes two aspects. One is the design of the two selections of decomposition features, that is, the speckle noise filtering; another is the selected features to perform the enhance processing, so more effective change information will obtain. The feasibility of the SWT-BIMF algorithm is verified by the measured SAR image data, and good experimental results are obtained.

  18. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    Directory of Open Access Journals (Sweden)

    Lu Ping-ping

    2014-06-01

    Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

  19. 利用高分辨率聚束模式TerraSAR-X影像的PSInSAR监测地表变形%Monitoring Land Deformation Using PSInSAR with TerraSAR-X High Resolution Spotlight SAR Images

    Institute of Scientific and Technical Information of China (English)

    李永生; 张景发; 罗毅; 姜文亮

    2012-01-01

    利用20景于2010-03~2010-11期间采集的高分辨率聚束(1m分辨率)模式的TerraSAR-X SAR数据,采用永久散射体干涉测量技术(PSInSAR)获取了西藏羊八井地区由地热电站开采地下水引起的地面沉降。结果显示,羊八井地热电站周边及地热开采井地区在2010年期间的地面沉降速率最大达到25mm·a-1,而盆地其他地区的地面平均沉降速率为1mm·a-1。将其与ASAR获取的平均沉降速率结果对比,两者的相关性达到了0.76,这说明TerraSAR-X高分辨率SAR数据不仅可以提供高密度PS点,而且更好地体现了散射体的细节变化和微量位移情况。%Persistent scatterer InSAR was used to detect surface subsidence in the the Yangbajing geothermal power plant due to extraction of ground water with area aroun twent resolution TerraSAR-X spotlight SAR images collected between March and November y hig 2010 d h The results suggest that land subsidence in the areas of geothermal wells is up to 25 mm · a^-1 whilst the subsidence in the basin is less than 1 mm · a^- 1. And the correlation between TerraSAR-X and ASAR derived mean velocities is 0.76. TerraSAR-X high resolution spot- light SAR images can provide higher density of PS points than ASAR data, and also can re- veal the detail change and micro-displacement in a single ground object.

  20. Extraction of Coastlines with Fuzzy Approach Using SENTINEL-1 SAR Image

    Science.gov (United States)

    Demir, N.; Kaynarca, M.; Oy, S.

    2016-06-01

    Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS) Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the LIDAR points of

  1. Haystack Ultrawideband Satellite Imaging Radar

    Science.gov (United States)

    2014-09-01

    enable long-range imaging. In 2013, a major upgrade to the facility was completed, adding a millimeter - wave W-band radar capability to Haystack’s X...diameter antenna was completely rebuilt to provide a 100 μm root-mean-square (rms) surface accuracy to support operation at the 3 mm wave - length (W...electromagnetic wave propagation through the troposphere. − The signal processing system lev- eraged Lincoln Laboratory‘s Radar Open Systems

  2. Change detection in satellite images

    Science.gov (United States)

    Thonnessen, U.; Hofele, G.; Middelmann, W.

    2005-05-01

    Change detection plays an important role in different military areas as strategic reconnaissance, verification of armament and disarmament control and damage assessment. It is the process of identifying differences in the state of an object or phenomenon by observing it at different times. The availability of spaceborne reconnaissance systems with high spatial resolution, multi spectral capabilities, and short revisit times offer new perspectives for change detection. Before performing any kind of change detection it is necessary to separate changes of interest from changes caused by differences in data acquisition parameters. In these cases it is necessary to perform a pre-processing to correct the data or to normalize it. Image registration and, corresponding to this task, the ortho-rectification of the image data is a further prerequisite for change detection. If feasible, a 1-to-1 geometric correspondence should be aspired for. Change detection on an iconic level with a succeeding interpretation of the changes by the observer is often proposed; nevertheless an automatic knowledge-based analysis delivering the interpretation of the changes on a semantic level should be the aim of the future. We present first results of change detection on a structural level concerning urban areas. After pre-processing, the images are segmented in areas of interest and structural analysis is applied to these regions to extract descriptions of urban infrastructure like buildings, roads and tanks of refineries. These descriptions are matched to detect changes and similarities.

  3. THE REALIZATION OF THE PPP AUTOFOCUS METHOD IN PFA FOR SPOTLIGHT MODE SAR IMAGING

    Institute of Scientific and Technical Information of China (English)

    Fu Wenxian; Hong Wen; Li Shaohong

    2002-01-01

    This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation. Mathematical analysis and computer simulations show the above mentioned motion kinds and their corresponding damages on spotlight mode SAR imaging. Based on this analysis, a single PPP is introduced for spotlight mode SAR imaging with the PFA on the assumption that relative rotation between APC and imaged scene is uniform. The selected single point is used first to correct the quadratic and higher order phase errors and then to adjust the linear errors. After this compensation, the space-invariant phase errors caused by translation are almost corrected. Finally results are presented with the simulated data.

  4. THE REALIZATION OF THE PPP AUTOFOCUS METHOD IN PFA FOR SPOTLIGHT MODE SAR IMAGING

    Institute of Scientific and Technical Information of China (English)

    FuWenxian; HongWen; 等

    2002-01-01

    This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation.Mathematical analysis and computer simulations show the sbove mentioned motion kinds and their corresponding damages on spotlight mode SAR imaging.Based on this analysis, a single PPP is introduced for spotlight mode SAR imaging with the PFA on the assumption that relative rotation between APC and imaged sceme is uniform.The selected single point is used first to correct the quadratic and higher order phase errors and then to adjust the linear errors.After this compensation, the space-invariant phase errors caused by translation are almost corrected.Finally results are presented with the simulated data.

  5. Compressed Sensing Imaging Algorithm for High-squint SAR Based on NCS Operator

    Directory of Open Access Journals (Sweden)

    Gu Fufei

    2016-02-01

    Full Text Available A novel compressed sensing imaging algorithm for high-squint Synthetic Aperture Radar (SAR based on a Nonlinear Chirp-Scaling (NCS operator is proposed. First, the echo signal of high-squint SAR is analyzed, and a novel imaging method based on the Nyquist-sampled echo signal is proposed. With the proposed method, the range migration is corrected and the coupling problem in the range and azimuth directions is solved. Then, to solve the problem of high-squint SAR imaging using undersampled echo signals, the NCS operator and compressed sensing algorithm based on this operator are constructed. Imaging results are obtained by solving an optimization problem. The proposed method can recover a sparse scene using undersampled echo data. Furthermore, it can recover a nonsparse scene using fully sampled data. Finally, simulations show the effectiveness of the proposed method.

  6. An Optimal Method For Wake Detection In SAR Images Using Radon Transformation Combined With Wavelet Filters

    CERN Document Server

    Krishnaveni, M; Subashini, P

    2009-01-01

    A new fangled method for ship wake detection in synthetic aperture radar (SAR) images is explored here. Most of the detection procedure applies the Radon transform as its properties outfit more than any other transformation for the detection purpose. But still it holds problems when the transform is applied to an image with a high level of noise. Here this paper articulates the combination between the radon transformation and the shrinkage methods which increase the mode of wake detection process. The latter shrinkage method with RT maximize the signal to noise ratio hence it leads to most optimal detection of lines in the SAR images. The originality mainly works on the denoising segment of the proposed algorithm. Experimental work outs are carried over both in simulated and real SAR images. The detection process is more adequate with the proposed method and improves better than the conventional methods.

  7. Inventory and state of activity of rockglaciers in the Ile and Kungöy Ranges of Northern Tien Shan from satellite SAR interferometry

    Science.gov (United States)

    Strozzi, Tazio; Caduff, Rafael; Kääb, Andreas; Bolch, Tobias

    2017-04-01

    other slope instabilities into different classes (e.g. cm/day, dm/month, cm/month and cm/yr). More sophisticated SAR interferometric approaches like Persistent Scatterer Interferometry (PSI) or Short Baseline Interferometry (SBAS) are only able to detect points moving with velocities below a few cm/yr respectively several dm/yr in the Line-Of-Sight (LOS) direction, because of phase unwrapping issues. For our analysis in the Tien Shan we considered SAR interferograms with short baselines and acquisition time intervals between 1 day and approximately one year. Satellite images from the ERS-1/2 tandem mission in 1998-1999, ALOS-1 PALSAR-1 between 2006-2010 (46 days nominal repeat cycle), ALOS-2 PALSAR-2 between 2014 and 2016 (14 days nominal repeat cycle), and Sentinel-1 between 2015 and 2016 (12 days nominal repeat cycle) were used. Images acquired along both ascending and descending geometries and during summer (snow-free) and winter (frozen snow) conditions were employed. For topographic reference and orthorectification we computed in-house a Digital Elevation Model from TanDEM-X acquisitions of ascending and descending orbits. Phase unwrapping to derive the LOS displacement was attempted only locally for selected landforms with a moderate (e.g. rate of motion. Our inventory of rockglaciers and other periglacial processes in the Northern Tien Shan includes so far more than 500 objects over an area of more than 3000 km2. In future, our inventory will be compared to other existing inventories compiled in field or with air photos. In addition, the long-term monitoring of rockglacier motion will be performed taking advantage of the synergies between repeat optical and radar satellite data. The combined approach is useful for the confirmation of the activity, filling spatial and/or temporal gaps, computing the historical fast motion of rockglaciers from optical data and the slow motion from SAR interferometry, and to compare multi-annual rates of motion (optical data) with

  8. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  9. Target Detection in SAR Images Based on a Level Set Approach

    Energy Technology Data Exchange (ETDEWEB)

    Marques, Regis C.P.; Medeiros, Fatima N.S.; Ushizima, Daniela M.

    2008-09-01

    This paper introduces a new framework for point target detection in synthetic aperture radar (SAR) images. We focus on the task of locating reflective small regions using alevel set based algorithm. Unlike most of the approaches in image segmentation, we address an algorithm which incorporates speckle statistics instead of empirical parameters and also discards speckle filtering. The curve evolves according to speckle statistics, initially propagating with a maximum upward velocity in homogeneous areas. Our approach is validated by a series of tests on synthetic and real SAR images and compared with three other segmentation algorithms, demonstrating that it configures a novel and efficient method for target detection purpose.

  10. Internal waves and vortices in satellite images

    CERN Document Server

    Sparavigna, Amelia Carolina

    2012-01-01

    Some recent papers proposed the use of the satellite images of Google Earth in teaching physics, in particular to see some behaviours of waves. Reflection, refraction, diffraction and interference are easy to be found in these satellite maps. Besides Google Earth, other sites exist, such as Earth Observatory or Earth Snapshot, suitable for illustrating the large-scale phenomena in atmosphere and oceans In this paper, we will see some examples for teaching surface and internal sea waves, and internal waves and the K\\'arm\\'an vortices in the atmosphere. Aim of this proposal is attracting the interest of students of engineering schools to the physics of waves.

  11. AO corrected satellite imaging from Mount Stromlo

    Science.gov (United States)

    Bennet, F.; Rigaut, F.; Price, I.; Herrald, N.; Ritchie, I.; Smith, C.

    2016-07-01

    The Research School of Astronomy and Astrophysics have been developing adaptive optics systems for space situational awareness. As part of this program we have developed satellite imaging using compact adaptive optics systems for small (1-2 m) telescopes such as those operated by Electro Optic Systems (EOS) from the Mount Stromlo Observatory. We have focused on making compact, simple, and high performance AO systems using modern high stroke high speed deformable mirrors and EMCCD cameras. We are able to track satellites down to magnitude 10 with a Strehl in excess of 20% in median seeing.

  12. Imaging Formation Algorithm of the Ground and Space-Borne Hybrid BiSAR Based on Parameters Estimation from Direct Signal

    Directory of Open Access Journals (Sweden)

    Qingjun Zhang

    2014-01-01

    Full Text Available This paper proposes a novel image formation algorithm for the bistatic synthetic aperture radar (BiSAR with the configuration of a noncooperative transmitter and a stationary receiver in which the traditional imaging algorithm failed because the necessary imaging parameters cannot be estimated from the limited information from the noncooperative data provider. In the new algorithm, the essential parameters for imaging, such as squint angle, Doppler centroid, and Doppler chirp-rate, will be estimated by full exploration of the recorded direct signal (direct signal is the echo from satellite to stationary receiver directly from the transmitter. The Doppler chirp-rate is retrieved by modeling the peak phase of direct signal as a quadratic polynomial. The Doppler centroid frequency and the squint angle can be derived from the image contrast optimization. Then the range focusing, the range cell migration correction (RCMC, and the azimuth focusing are implemented by secondary range compression (SRC and the range cell migration, respectively. At last, the proposed algorithm is validated by imaging of the BiSAR experiment configured with china YAOGAN 10 SAR as the transmitter and the receiver platform located on a building at a height of 109 m in Jiangsu province. The experiment image with geometric correction shows good accordance with local Google images.

  13. Construction of SAR Image Library System Based on ORACLE and Arcsde%基于ORACLE和Arcsde的SAR影像库系统构建

    Institute of Scientific and Technical Information of China (English)

    石雪冬; 周霁进

    2013-01-01

    Synthetic Aperture Radar is a kind of microwave imaging system with advantages of all day long and all weather observation , multi - frequency band, multi - polarization and multiple points of view, etc. At present, in view of the typical feature analysis of SAR image library system research, this paper collects all kinds of satellite - borne SAR image data, analyses the space database and spatial data engine technology to construct the SAR image library system based on Oracle and ArcSDE integration technology according to the ArcGIS Engine and. net core language C# programming environment. SAR image library system realizes the effective storage between image data and highly efficient storage between meta data and image data, and provides an efficient platform for extract and interpret the typical feature information.%合成孔径雷达(Synthetic Aperture Radar,SAR)是一种微波的成像系统,具有全天时、全天候观测以及多频段、多极化和多视角等优点.本文在收集各类星载SAR影像数据基础上,通过对空间数据库和空间数据引擎技术的分析,在ArcGIS Engine和.NET的核心语言C#编程环境下,构建了基于Oracle和ArcSDE集成技术的SAR影像库系统.SAR影像库系统实现了影像数据之间的有效存储,以及元数据与影像数据的高效、统一存储,并为典型地物的特征信息提取和判读工具的形成提供了一个高效平台.

  14. Development of a Methodology for Mapping Forest Height and Biomass Using Satellite Based SAR and Lidar Data

    Science.gov (United States)

    Hilbert, Claudia; Schmullius, Christiane

    2010-12-01

    This paper presents first results of a study investigating satellite, multifrequent radar and lidar data for characterising the three-dimensional forest structure. Biomass is an important structural parameter to asses the carbon pool of forests. The synergy of lidar and SAR data for forest biomass mapping is promising. The study introduced here aims to combine TerraSAR-X, ALOS PALSAR and ICESat/GLAS data. Some preliminary results for the test site in Thuringian Forest, a low mountain range in eastern Germany, with a focus on the GLAS data will be described. Two methods for filtering invalid GLAS shots are investigated. Moreover, different ICESat/GLAS waveforms parameters were calculated and compared to an airborne lidar based Digital Height Model (DHM) and a forest inventory data base.

  15. SAR Computation inside Fetus by RF Coil during MR Imaging Employing Realistic Numerical Pregnant Woman Model

    Science.gov (United States)

    Kikuchi, Satoru; Saito, Kazuyuki; Takahashi, Masaharu; Ito, Koichi; Ikehira, Hiroo

    This paper presents the computational electromagnetic dosimetry inside an anatomically based pregnant woman models exposed to electromagnetic wave during magnetic resonance imaging. The two types of pregnant woman models corresponding to early gestation and 26 weeks gestation were used for this study. The specific absorption rate (SAR) in and around a fetus were calculated by radiated electromagnetic wave from highpass and lowpass birdcage coil. Numerical calculation results showed that high SAR region is observed at the body in the vicinity of gaps of the coil, and is related to concentrated electric field in the gaps of human body such as armpit and thigh. Moreover, it has confirmed that the SAR in the fetus is less than International Electrotechnical Commission limit of 10W/kg, when whole-body average SARs are 2W/kg and 4W/kg, which are the normal operating mode and first level controlled operating mode, respectively.

  16. Antarctica: measuring glacier velocity from satellite images.

    Science.gov (United States)

    Lucchitta, B K; Ferguson, H M

    1986-11-28

    Many Landsat images of Antarctica show distinctive flow and crevasse features in the floating part of ice streams and outlet glaciers immediately below their grounding zones. Some of the features, which move with the glacier or ice stream, remain visible over many years and thus allow time-lapse measurements of ice velocities. Measurements taken from Landsat images of features on Byrd Glacier agree well with detailed ground and aerial observations. The satellite-image technique thus offers a rapid and cost-effective method of obtaining average velocities, to a first order of accuracy, of many ice streams and outlet glaciers near their termini.

  17. A neuromorphic approach to satellite image understanding

    Science.gov (United States)

    Partsinevelos, Panagiotis; Perakakis, Manolis

    2014-05-01

    Remote sensing satellite imagery provides high altitude, top viewing aspects of large geographic regions and as such the depicted features are not always easily recognizable. Nevertheless, geoscientists familiar to remote sensing data, gradually gain experience and enhance their satellite image interpretation skills. The aim of this study is to devise a novel computational neuro-centered classification approach for feature extraction and image understanding. Object recognition through image processing practices is related to a series of known image/feature based attributes including size, shape, association, texture, etc. The objective of the study is to weight these attribute values towards the enhancement of feature recognition. The key cognitive experimentation concern is to define the point when a user recognizes a feature as it varies in terms of the above mentioned attributes and relate it with their corresponding values. Towards this end, we have set up an experimentation methodology that utilizes cognitive data from brain signals (EEG) and eye gaze data (eye tracking) of subjects watching satellite images of varying attributes; this allows the collection of rich real-time data that will be used for designing the image classifier. Since the data are already labeled by users (using an input device) a first step is to compare the performance of various machine-learning algorithms on the collected data. On the long-run, the aim of this work would be to investigate the automatic classification of unlabeled images (unsupervised learning) based purely on image attributes. The outcome of this innovative process is twofold: First, in an abundance of remote sensing image datasets we may define the essential image specifications in order to collect the appropriate data for each application and improve processing and resource efficiency. E.g. for a fault extraction application in a given scale a medium resolution 4-band image, may be more effective than costly

  18. PRIMA Platform capability for satellite missions in LEO and MEO (SAR, Optical, GNSS, TLC, etc.)

    Science.gov (United States)

    Logue, T.; L'Abbate, M.

    2016-12-01

    PRIMA (Piattaforma Riconfigurabile Italiana Multi Applicativa) is a multi-mission 3-axis stabilized Platform developed by Thales Alenia Space Italia under ASI contract.PRIMA is designed to operate for a wide variety of applications from LEO, MEO up to GEO and for different classes of satellites Platform Family. It has an extensive heritage in flight heritage (LEO and MEO Satellites already fully operational) in which it has successfully demonstrated the flexibility of use, low management costs and the ability to adapt to changing operational conditions.The flexibility and modularity of PRIMA provides unique capability to satisfy different Payload design and mission requirements, thanks to the utilization of recurrent adaptable modules (Service Module-SVM, Propulsion Module-PPM, Payload Module-PLM) to obtain mission dependent configuration. PRIMA product line development is continuously progressing, and is based on state of art technology, modular architecture and an Integrated Avionics. The aim is to maintain and extent multi-mission capabilities to operate in different environments (LEO to GEO) with different payloads (SAR, Optical, GNSS, TLC, etc.). The design is compatible with a wide range of European and US equipment suppliers, thus maximising cooperation opportunity. Evolution activities are mainly focused on the following areas: Structure: to enable Spacecraft configurations for multiple launch; Thermal Control: to guarantee thermal limits for new missions, more demanding in terms of environment and payload; Electrical: to cope with higher power demand (e.g. electrical propulsion, wide range of payloads, etc.) considering orbital environment (e.g. lighting condition); Avionics : AOCS solutions optimized on mission (LEO observation driven by agility and pointing, agility not a driver for GEO). Use of sensors and actuators tailored for specific mission and related environments. Optimised Propulsion control. Data Handling, SW and FDIR mission customization

  19. An Algorithm for Ship Wake Detection from the SAR Images Using the Radon Transform and Morphological Image Processing

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Using the Rador transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linesr texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.

  20. A sparsity-driven approach for joint SAR imaging and phase error correction.

    Science.gov (United States)

    Önhon, N Özben; Cetin, Müjdat

    2012-04-01

    Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed images. The application of interest in this paper is synthetic aperture radar (SAR) imaging, which particularly suffers from motion-induced model errors. These types of errors result in phase errors in SAR data, which cause defocusing of the reconstructed images. Particularly focusing on imaging of fields that admit a sparse representation, we propose a sparsity-driven method for joint SAR imaging and phase error correction. Phase error correction is performed during the image formation process. The problem is set up as an optimization problem in a nonquadratic regularization-based framework. The method involves an iterative algorithm, where each iteration of which consists of consecutive steps of image formation and model error correction. Experimental results show the effectiveness of the approach for various types of phase errors, as well as the improvements that it provides over existing techniques for model error compensation in SAR.

  1. Imaging artificial satellites: An observational challenge

    Science.gov (United States)

    Smith, D. A.; Hill, D. C.

    2016-10-01

    According to the Union of Concerned Scientists, as of the beginning of 2016 there are 1381 active satellites orbiting the Earth, and the United States' Space Surveillance Network tracks about 8000 manmade orbiting objects of baseball-size and larger. NASA estimates debris larger than 1 cm to number more than half a million. The largest ones can be seen by eye—unresolved dots of light that move across the sky in minutes. For most astrophotographers, satellites are annoying streaks that can ruin hours of work. However, capturing a resolved image of an artificial satellite can pose an interesting challenge for a student, and such a project can provide connections between objects in the sky and commercial and political activities here on Earth.

  2. The 2010 MW 6.9 Yushu (Qinghai, China) earthquake: constraints from InSAR, bodywave modeling and satellite imagery

    Science.gov (United States)

    Parsons, B. E.; Li, Z.; Elliott, J. R.; Barisin, I.; Feng, W.; Jackson, J. A.; Song, X.; Walters, R. J.; Zhang, P.

    2010-12-01

    A large earthquake (MW = 6.9) struck the county of Yushu, Qinghai, China on 13 April 2010, causing 2,220 fatalities and over 12,000 injured. We have used a combination of ALOS and Envisat SAR data to model the fault geometry and slip distribution of this event, using high-resolution satellite imagery and bodywave modelling to provide further information. Preliminary observations were first posted on the internet on 20 April 2010. The fault on which the earthquake occurred can be traced precisely using SPOT 5 (2.5 m resolution) imagery and SAR image offsets, interferometric coherence and phase discontinuities. On this basis the fault was most simply divided into three segments. The dips of the fault segments were obtained from elastic dislocation models with uniform slip; the southeast segment, on which the largest slip occurred, and northwest segment are near vertical, with the central segment dipping about 75° to the southwest. Slip was almost pure left-lateral. The fault geometry was then fixed and the slip distribution that best-fits the InSAR phase measurements determined. Slip occurs mainly in the upper 10 km, with a maximum slip of ~2 m at a depth of 3 km on the southeast segment. Near-surface slip (upper 1 km of the model) agrees well with field observations of offsets on the southeast segment. The geodetically-determined and seismic moments are in reasonable agreement (2.1 ± 0.2 × 1019 N m). However, rupture lengths of 35-40 km were estimated immediately after the earthquake from the seismic moment together with a magnitude of slip from surface observations and assumed seismogenic layer thicknesses, whereas the interferograms showed slip must have occurred over a length of 70-75 km. The apparent discrepancy can be explained in terms of the non-uniform distribution of moment release on the fault. There are three main patches of moment release along the length of the fault. We believe the northwest patch may be due to the aftershock (M0 = ~0.2 × 1019 N m

  3. Polarimetric Contextual Classification of PolSAR Images Using Sparse Representation and Superpixels

    Directory of Open Access Journals (Sweden)

    Jilan Feng

    2014-07-01

    Full Text Available In recent years, sparse representation-based techniques have shown great potential for pattern recognition problems. In this paper, the problem of polarimetric synthetic aperture radar (PolSAR image classification is investigated using sparse representation-based classifiers (SRCs. We propose to take advantage of both polarimetric information and contextual information by combining sparsity-based classification methods with the concept of superpixels. Based on polarimetric feature vectors constructed by stacking a variety of polarimetric signatures and a superpixel map, two strategies are considered to perform polarimetric-contextual classification of PolSAR images. The first strategy starts by classifying the PolSAR image with pixel-wise SRC. Then, spatial regularization is imposed on the pixel-wise classification map by using majority voting within superpixels. In the second strategy, the PolSAR image is classified by taking superpixels as processing elements. The joint sparse representation-based classifier (JSRC is employed to combine the polarimetric information contained in feature vectors and the contextual information provided by superpixels. Experimental results on real PolSAR datasets demonstrate the feasibility of the proposed approaches. It is proven that the classification performance is improved by using contextual information. A comparison with several other approaches also verifies the effectiveness of the proposed approach.

  4. Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching

    Directory of Open Access Journals (Sweden)

    Jian-Jun Zhu

    2008-10-01

    Full Text Available The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction, with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground. Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more

  5. Multi-Core DSP Based Parallel Architecture for FMCW SAR Real-Time Imaging

    Directory of Open Access Journals (Sweden)

    C. F. Gu

    2015-12-01

    Full Text Available This paper presents an efficient parallel processing architecture using multi-core Digital Signal Processor (DSP to improve the capability of real-time imaging for Frequency Modulated Continuous Wave Synthetic Aperture Radar (FMCW SAR. With the application of the proposed processing architecture, the imaging algorithm is modularized, and each module is efficiently realized by the proposed processing architecture. In each module, the data processing of different cores is executed in parallel, also the data transmission and data processing of each core are synchronously carried out, so that the processing time for SAR imaging is reduced significantly. Specifically, the time of corner turning operation, which is very time-consuming, is ignored under computationally intensive case. The proposed parallel architecture is applied to a compact Ku-band FMCW SAR prototype to achieve real-time imageries with 34 cm x 51 cm (range x azimuth resolution.

  6. SAR images classification method based on Dempster-Shafer theory and kernel estimate

    Institute of Scientific and Technical Information of China (English)

    He Chu; Xia Guisong; Sun Hong

    2007-01-01

    To study the scene classification in the Synthetic Aperture Radar (SAR) image, a novel method based on kernel estimate, with the Markov context and Dempster-Shafer evidence theory is proposed.Initially, a nonparametric Probability Density Function (PDF) estimate method is introduced, to describe the scene of SAR images.And then under the Markov context, both the determinate PDF and the kernel estimate method are adopted respectively, to form a primary classification.Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification.Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification.Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results.Experimental results on real SAR images illustrate a rather impressive performance.

  7. Edge Detection of PolSAR Image Based on Stochastic Distance

    Directory of Open Access Journals (Sweden)

    WANG Qing

    2015-07-01

    Full Text Available A new edge detection methodology in PolSAR images is proposed, which is based on stochastic distance in the statistical theory and combined with complex Wishart distribution. Its main principle is inspired from the phenomenon that stochastic distance of two classes separated by an edge is closely related to the edge direction and the contrast of two classes. Simulation experiments are carried out to analyze the performance of the proposed methods. Results prove that methods have better capabilities in edge orientation and edge positioning than common used methods. Then, the proposed detection procedure is tested on a simulated PolSAR image with the complex Wishart distribution, as well as an airborne fully polarimetric SAR image.

  8. Polarimetric SAR Image Object Segmentation via Level Set with Stationary Global Minimum

    Directory of Open Access Journals (Sweden)

    Wen Yang

    2010-01-01

    Full Text Available We present a level set-based method for object segmentation in polarimetric synthetic aperture radar (PolSAR images. In our method, a modified energy functional via active contour model is proposed based on complex Gaussian/Wishart distribution model for both single-look and multilook PolSAR images. The modified functional has two interesting properties: (1 the curve evolution does not enter into local minimum; (2 the level set function has a unique stationary convergence state. With these properties, the desired object can be segmented more accurately. Besides, the modified functional allows us to set an effective automatic termination criterion and makes the algorithm more practical. The experimental results on synthetic and real PolSAR images demonstrate the effectiveness of our method.

  9. Classification of agricultural fields using time series of dual polarimetry TerraSAR-X images

    Directory of Open Access Journals (Sweden)

    S. Mirzaee

    2014-10-01

    Full Text Available Due to its special imaging characteristics, Synthetic Aperture Radar (SAR has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient.

  10. Design and Implementation of the HJ-1-C Satellite SAR Full-power Radiation Test

    OpenAIRE

    Zhang Hua-chun; Tao Xin; Ni Jiang; Yu Wei-dong

    2014-01-01

    In this paper, the HJ-1-C SAR full-power radiation test design is presented. For the new problems caused by SAR high-power concentrated emissions, the radar-receiving channel-leakage power test is proposed to ensure the safety of the radar-receiving path, and the transceiver channel closed-loop radar system test is discussed. The experimental results show that the proposed HJ-1-C SAR full-power radiation test scheme is reasonable and feasible, with the desired outcome.

  11. Design and Implementation of the HJ-1-C Satellite SAR Full-power Radiation Test

    Directory of Open Access Journals (Sweden)

    Zhang Hua-chun

    2014-06-01

    Full Text Available In this paper, the HJ-1-C SAR full-power radiation test design is presented. For the new problems caused by SAR high-power concentrated emissions, the radar-receiving channel-leakage power test is proposed to ensure the safety of the radar-receiving path, and the transceiver channel closed-loop radar system test is discussed. The experimental results show that the proposed HJ-1-C SAR full-power radiation test scheme is reasonable and feasible, with the desired outcome.

  12. Comparing C- and L-band SAR images for sea ice motion estimation

    Science.gov (United States)

    Lehtiranta, J.; Siiriä, S.; Karvonen, J.

    2015-02-01

    Pairs of consecutive C-band synthetic-aperture radar (SAR) images are routinely used for sea ice motion estimation. The L-band radar has a fundamentally different character, as its longer wavelength penetrates deeper into sea ice. L-band SAR provides information on the seasonal sea ice inner structure in addition to the surface roughness that dominates C-band images. This is especially useful in the Baltic Sea, which lacks multiyear ice and icebergs, known to be confusing targets for L-band sea ice classification. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal cross-correlation (MCC) approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.

  13. a New 2d Otsu for Water Extraction from SAR Image

    Science.gov (United States)

    Guo, Y.; Zhang, J.

    2017-09-01

    SAR image segmentation is a crucial step that heavily influences the performance of image interpretation. The texture factor to replace the neighborhood mean dimension in the traditional Otsu method is proposed in this work, aiming at the problem that the SAR image has unique characteristics and the original 2D Otsu method only considers the pixel neighborhood mean information. In this paper, TerraSAR image with the single band and single polarization is used to water extraction. Firstly, the semantic function is used to analyze the structural characteristics of the sample image to determine the optimal parameters of the texture information extraction. Then, calculate the textural measures such as contrast, entropy, homogeneity, mean and second moment based on gray level co-occurrence matrix(GLCM) method. The results are compared with the artificially marked images and the results of the original 2D Otsu.The experimental results achieve higher objective values, which shows the proposed algorithm using texture factor has a high practical value for SAR Image water segmentation.

  14. Speckle Filtering in PolSAR Images by Enhanced Wavelet Thresholding

    Science.gov (United States)

    Boutarfa, Souhila; Bouchemakh, Lynda; Smara, Youcef

    2016-08-01

    The PolSAR images are affected by a noise called speckle, which deteriorates image quality and complicates image interpretation. The polarimetric filtering is a necessary treatment prior to analysis that allows to reduce speckle and to obtain an improved image quality.In this paper, we present a polarimetric speckle filtering method based on enhancement of wavelet thresholding, hard and soft thresholding using directional coefficients improvement to reduce speckle without destroying the information. This algorithm is based on the classification of significant coefficients and applying the thresholding to obtain a better image quality.The methods are applied to the three polarimetric E-SAR images acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band and the fully polarimetric RADARSAT-2 images acquired on Algiers, Algeria, in C-band.To evaluate the performance of each filter, we based it on the following criteria: smoothing homogeneous areas, preserving structural characteristics of objects and maintaining the information.

  15. CLASSIFIER FUSION OF HIGH-RESOLUTION OPTICAL AND SYNTHETIC APERTURE RADAR (SAR SATELLITE IMAGERY FOR CLASSIFICATION IN URBAN AREA

    Directory of Open Access Journals (Sweden)

    T. Alipour Fard

    2014-10-01

    Full Text Available This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular application. In this paper, two category of features are generate and six classifier fusion operators implemented and evaluated. Implementation results show significant improvement in the classification accuracy.

  16. SAR image segmentation with entropy ranking based adaptive semi-supervised spectral clustering

    Science.gov (United States)

    Zhang, Xiangrong; Yang, Jie; Hou, Biao; Jiao, Licheng

    2010-10-01

    Spectral clustering has become one of the most popular modern clustering algorithms in recent years. In this paper, a new algorithm named entropy ranking based adaptive semi-supervised spectral clustering for SAR image segmentation is proposed. We focus not only on finding a suitable scaling parameter but also determining automatically the cluster number with the entropy ranking theory. Also, two kinds of constrains must-link and cannot-link based semi-supervised spectral clustering is applied to gain better segmentation results. Experimental results on SAR images show that the proposed method outperforms other spectral clustering algorithms.

  17. TerraSAR-X mission

    Science.gov (United States)

    Werninghaus, Rolf

    2004-01-01

    The TerraSAR-X is a German national SAR- satellite system for scientific and commercial applications. It is the continuation of the scientifically and technologically successful radar missions X-SAR (1994) and SRTM (2000) and will bring the national technology developments DESA and TOPAS into operational use. The space segment of TerraSAR-X is an advanced high-resolution X-Band radar satellite. The system design is based on a sound market analysis performed by Infoterra. The TerraSAR-X features an advanced high-resolution X-Band Synthetic Aperture Radar based on the active phased array technology which allows the operation in Spotlight-, Stripmap- and ScanSAR Mode with various polarizations. It combines the ability to acquire high resolution images for detailed analysis as well as wide swath images for overview applications. In addition, experimental modes like the Dual Receive Antenna Mode allow for full-polarimetric imaging as well as along track interferometry, i.e. moving target identification. The Ground Segment is optimized for flexible response to (scientific and commercial) User requests and fast image product turn-around times. The TerraSAR-X mission will serve two main goals. The first goal is to provide the strongly supportive scientific community with multi-mode X-Band SAR data. The broad spectrum of scientific application areas include Hydrology, Geology, Climatology, Oceanography, Environmental Monitoring and Disaster Monitoring as well as Cartography (DEM Generation) and Interferometry. The second goal is the establishment of a commercial EO-market in Europe which is driven by Infoterra. The commercial goal is the development of a sustainable EO-business so that the e.g. follow-on systems can be completely financed by industry from the profit. Due to its commercial potential, the TerraSAR-X project will be implemented based on a public-private partnership with the Astrium GmbH. This paper will describe first the mission objectives as well as the

  18. Change detection of polarimetric SAR images based on the KummerU Distribution

    Science.gov (United States)

    Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

    2014-11-01

    In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

  19. A despeckle filter for the Cassini SAR images of Titan's surface

    Science.gov (United States)

    Bratsolis, Emmanuel; Solomonidou, Anezina; Bampasidis, Georgios; Le Mouelic, Stephane; Sotin, Christophe; Coustenis, Athena; Moussas, Xenophon; Kyriakopoulos, Konstantinos

    2010-05-01

    Cassini carries a multimode Ku-band (13.78 GHz) radar instrument designed to probe the surface of Titan and that of other targets in the Saturn system in four operating modes: imaging, altimetry, scatterometry, and radiometry. The Synthetic Aperture Radar (SAR) mode is used at altitudes under ~4000 km, resulting in spatial resolution ranging from ~350 m to >1 km. Images are acquired either left or right of nadir using 2-7 looks. A swath 120-450 km wide is created from 5 antenna beams. SAR coverage is dependent on spacecraft range and orbital geometry. Radar backscatter variations in SAR images can be interpreted in terms of variations of surface slope, near-surface roughness, or near-surface dielectric properties. The images obtained using SAR revealed that Titan has very complex surface (Elachi et al. 2005). A filtering technique is applied to obtain the restored image. One of the major problems hampering the derivation of meaningful texture information from SAR imagery is the speckle noise. It overlays "real" structures and causes gray value variations even in homogeneous parts of the image. Our method is based on probabilistic methods and regards an image as a random element drawn from a prespecified set of possible images. The TSPR (Total Sum Preserving Regularization) filter used here is based on a membrane model Markov random field approximation with a Gaussian conditional probability density function optimized by a synchronous local iterative method. The final form of despeckling gives a sum-preserving regularization for the pixel values of the image. The TSPR method preserves the mean values of local homogeneous regions and decreases the standard deviation up to six times (Bratsolis and Sigelle, 2003). The despeckle filter can be used as intermediate stage for the extraction of meaningful regions that correspond to structural units in the scene or distinguish objects of interest (Bratsolis, 2009). References E. Bratsolis, and M. Sigelle, "Fast SAR Image

  20. Developing Geostationary Satellite Imaging at Lowell Observatory

    Science.gov (United States)

    van Belle, G.

    2016-09-01

    Lowell Observatory operates the Navy Precision Optical Interferometer (NPOI), and owns & operates the Discovery Channel Telescope (DCT). This unique & necessary combination of facilities positions Lowell to develop a robust program of observing geostationary, GPS-plane, and other high-altitude (&1000mi) satellites. NPOI is a six-beam long-baseline optical interferometer, located in Flagstaff, Arizona; the facility is supported by a partnership between Lowell Observatory, the US Naval Observatory, and the Naval Research Laboratory. NPOI operates year-round in the visible with baselines between 8 and 100 meters (up to 432m is available), conducting programs of astronomical research and imaging technology development. NPOI is the only such facility as yet to directly observe geostationary satellites, enabling milliarcsecond resolution of these objects. To enhance this capability towards true imaging of geosats, an ongoing program of facility upgrades will be outlined. These upgrades include AO-assisted 1.0-m apertures feeding each beam line, and new near-infrared instrumentation on the back end. The large apertures will enable `at-will' observations of objects brighter than mK = 8:3 in the near-IR, corresponding to brighter than mV = 11:3 in the visible. At its core, the system is enabled by a `wavelength-baseline bootstrapping' approach discussed herein. A complementary pilot imaging study of visible speckle and aperture masked imaging at Lowell's 4.3-m DCT, for constraining the low-spatial frequency imaging information, is also outlined.

  1. 地球同步轨道双基SAR成像方法%Imaging Algorithm for GEO-LEO Bistatic SAR

    Institute of Scientific and Technical Information of China (English)

    宋舒; 马仑; 廖桂生

    2013-01-01

    GEO-LEO distributed spaceborne SAR systems,in which GEO satellite is used as illuminator and LEO satellite only used as signal receiver,have many advantages over conventional spaceborne SAR systems,such as wide observation range,strong anti-jamming and antidestruction ability and flexible networking.However,traditional monostatic SAR imaging algorithms are not applicable to such systems since the echo time delay is coupled with the azimuth position of the target.By analyzing the Doppler history of echo in detail,a novel SAR imaging algorithm for GEO-LEO bistatic spaceborne SAR systems is presented.According to the relationship between geometric distortion of target image and relative position of LEO satellite,the method divides the SAR echo into many patches along the range and the azimuth direction,respectively.For each patch,new range migration correction and matching functions are constructed to focus on the echo.Finally,geometric distortions of target images in each patch are corrected uniformly.The feasibility of the proposed method is verified by experimental results of simulation data.%地球同步轨道发射、低地球轨道接收体制的天基雷达系统具有观测范围广、抗摧毁和抗干扰能力强、组网灵活等优点.分析发现,该系统中回波的包络不仅与地表场景的斜距有关,还与其方位位置有关,传统的单基SAR成像方法不再适用.本文分析了回波包络的历程,给出了适用于该系统的SAR成像方法.该方法根据多普勒参数以及目标像的几何形变量随接收卫星与发射卫星几何位置关系的变化特征对数据沿方位以及距离向进行分块,并重新构造距离徙动校正和方位匹配函数对回波信号聚焦,最后进行几何形变校正.仿真数据的成像结果证明了方法的可行性.

  2. Heat equation inversion framework for average SAR calculation from magnetic resonance thermal imaging.

    Science.gov (United States)

    Alon, Leeor; Sodickson, Daniel K; Deniz, Cem M

    2016-10-01

    Deposition of radiofrequency (RF) energy can be quantified via electric field or temperature change measurements. Magnetic resonance imaging has been used as a tool to measure three dimensional small temperature changes associated with RF radiation exposure. When duration of RF exposure is long, conversion from temperature change to specific absorption rate (SAR) is nontrivial due to prominent heat-diffusion and conduction effects. In this work, we demonstrated a method for calculation of SAR via an inversion of the heat equation including heat-diffusion and conduction effects. This method utilizes high-resolution three dimensional magnetic resonance temperature images and measured thermal properties of the phantom to achieve accurate calculation of SAR. Accuracy of the proposed method was analyzed with respect to operating frequency of a dipole antenna and parameters used in heat equation inversion. Bioelectromagnetics. 37:493-503, 2016. © 2016 Wiley Periodicals, Inc.

  3. Ka-band InSAR Imaging and Analysis Based on IMU Data

    Directory of Open Access Journals (Sweden)

    Shi Jun

    2014-02-01

    Full Text Available Compared with other bands, the millimeter wave Interferometric Synthetic Aperture Radar (InSAR has high accuracy and small size, which is a hot topic in InSAR research. On the other hand, shorter wavelength causes difficulties in 2D imaging and interferometric phase extraction. In this study, the imaging and phase performance of the streaming Back Projection (BP method combined with IMU data are analyzed and discussed on the basis of actual Ka-band InSAR data. It is found that because the wavelength of the Ka-band is short, it is more sensitive to the antenna phase-center history. To ensure the phase-preserving capacity, the IMU data must be used with accurate motion error compensation. Furthermore, during data processing, we verify the flat-earth-removing capacity of the BP algorithm that calculates and compensates the master and slave antenna phase centers individually.

  4. A Modified Frequency Domain Imaging Method for One-stationary Bistatic SAR

    Directory of Open Access Journals (Sweden)

    Jin Ri-chu

    2014-04-01

    Full Text Available Bistatic Synthetic Aperture Radar (BiSAR in one-stationary mode has many advantages over the traditional monostatic SAR. Its echo, however, shows serious space variance in both range and azimuth directions due to its complex imaging geometry, making it hard to be processed by the frequency methods used in the monostatic SAR. To solve that problem, a method based on blocks and interpolation has been proposed by Wang Yu et al.. With this method, points can be well focused except for those located on the edge of each block. In this paper, a modified method is put forward, which adopts new block-dividing strategy and new mapping relationship in the interpolation. With the proposed method, points on the edge can also be well focused, making the quality of the final image greatly improved.

  5. An estimation method for InSAR interferometric phase combined with image auto-coregistration

    Institute of Scientific and Technical Information of China (English)

    LI Hai; LI Zhenfang; LIAO Guisheng; BAO Zheng

    2006-01-01

    In this paper we propose a method to estimate the InSAR interferometric phase of the steep terrain based on the terrain model of local plane by using the joint subspace projection technique proposed in our previous paper. The method takes advantage of the coherence information of neighboring pixel pairs to auto-coregister the SAR images and employs the projection of the joint signal subspace onto the corresponding joint noise subspace to estimate the terrain interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the interferometric phase (interferogram) of very steep terrain even if the coregistration error reaches one pixel. The effectiveness of the method is verified via simulated data and real data.

  6. Coupling Regular Tessellation with Rjmcmc Algorithm to Segment SAR Image with Unknown Number of Classes

    Science.gov (United States)

    Wang, Y.; Li, Y.; Zhao, Q. H.

    2016-06-01

    This paper presents a Synthetic Aperture Radar (SAR) image segmentation approach with unknown number of classes, which is based on regular tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC') algorithm. First of all, an image domain is portioned into a set of blocks by regular tessellation. The image is modeled on the assumption that intensities of its pixels in each homogeneous region satisfy an identical and independent Gamma distribution. By Bayesian paradigm, the posterior distribution is obtained to build the region-based image segmentation model. Then, a RJMCMC algorithm is designed to simulate from the segmentation model to determine the number of homogeneous regions and segment the image. In order to further improve the segmentation accuracy, a refined operation is performed. To illustrate the feasibility and effectiveness of the proposed approach, two real SAR image is tested.

  7. Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review

    Directory of Open Access Journals (Sweden)

    Xiaoli Ding

    2009-02-01

    Full Text Available Interferometric Synthetic Aperture Radar (InSAR is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.

  8. Matching suitable feature construction for SAR images based on evolutionary synthesis strategy

    Institute of Scientific and Technical Information of China (English)

    Bu Yanlong; Tang Geshi; Liu Hongfu; Pan Liang

    2013-01-01

    In the paper, a set of algorithms to construct synthetic aperture radar (SAR) matching suitable features are firstly proposed based on the evolutionary synthesis strategy. During the pro-cess, on the one hand, the indexes of primary matching suitable features (PMSFs) are designed based on the characteristics of image texture, SAR imaging and SAR matching algorithm, which is a process involving expertise;on the other hand, by designing a synthesized operation expression tree based on PMSFs, a much more flexible expression form of synthesized features is built, which greatly expands the construction space. Then, the genetic algorithm-based optimized searching process is employed to search the synthesized matching suitable feature (SMSF) with the highest efficiency, largely improving the optimized searching efficiency. In addition, the experimental results of the airborne synthetic aperture radar ortho-images of C-band and P-band show that the SMSFs gained via the algorithms can reflect the matching suitability of SAR images accurately and the matching probabilities of selected matching suitable areas of ortho-images could reach 99 ± 0.5%.

  9. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

    Science.gov (United States)

    Guo, Hao; Wu, Danni; An, Jubai

    2017-08-09

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

  10. Snow Water Equivalent Retrieval Using Multitemporal COSMO Skymed X-Band SAR Images To Inform Water Systems Operation

    Science.gov (United States)

    Denaro, S.; Del Gobbo, U.; Castelletti, A.; Tebaldini, S.; Monti Guarnieri, A.

    2015-12-01

    In this work, we explore the use of exogenous snow-related information for enhancing the operation of water facilities in snow dominated watersheds. Traditionally, such information is assimilated into short-to-medium term streamflow forecasts, which are then used to inform water systems operation. Here, we adopt an alternative model-free approach, where the policy is directly conditioned upon a small set of selected observational data able to surrogate the snow-pack dynamics. In snow-fed water systems, the Snow Water Equivalent (SWE) stored in the basin often represents the largest contribution to the future season streamflow. The SWE estimation process is challenged by the high temporal and spatial variability of snow-pack and snow properties. Traditional retrieval methods, based on few ground sensors and optical satellites, often fail at representing the spatial diversity of snow conditions over large basins and at producing continuous (gap-free) data at the high sample frequency (e.g. daily) required to optimally control water systems. Against this background, SWE estimates from remote sensed radar products stand out, being able to acquire spatial information with no dependence on cloud coverage. In this work, we propose a technique for retrieving SWE estimates from Synthetic Aperture Radar (SAR) Cosmo SkyMed X-band images: a regression model, calibrated on ground SWE measurements, is implemented on dry snow maps obtained through a multi-temporal approach. The unprecedented spatial scale of this application is novel w.r.t. state of the art radar analysis conducted on limited spatial domains. The operational value of the SAR retrieved SWE estimates is evaluated based on ISA, a recently developed information selection and assessment framework. The method is demonstrated on a snow-rain fed river basin in the Italian Alps. Preliminary results show SAR images have a good potential for monitoring snow conditions and for improving water management operations.

  11. Terrain topographic inversion using single-pass polarimetric SAR image data

    Institute of Scientific and Technical Information of China (English)

    JIN Yaqiu; LUO Lin

    2004-01-01

    The shift of polarization orientation angle ψat the maximum of co-polarized or cross-polarized back-scattering signature can be used to estimate the surface slopes. It has been utilized to generate the digital elevation mapping (DEM) and terrain topography using two-pass fully polarimetric SAR or interferometric SAR (INSAR) image data. This paper presents an approach to DEM inversion by using a single pass of polarimetric SAR data. The ψ shift is derived, by using the Mueller matrix solution, as a function of three Stokes parameters, /vs, Ihs, Us, which are measured by the SAR polarimetry. Using the Euler angles transformation, the orientation angle ψ is related to both the range and azimuth angles of the tilted surface and radar viewing geometry, as has been discussed by many authors. When only a single-pass SAR data is available, the adaptive thresholding method and image morphological thinning algorithm for linear textures are proposed to first determine the azimuth angle. Then, making use of full multi-grid algorithm, both the range and azimuth angles are utilized to solve the Poisson equation of DEM to produce the terrain topography.

  12. Embedded Implementation of VHR Satellite Image Segmentation.

    Science.gov (United States)

    Li, Chao; Balla-Arabé, Souleymane; Ginhac, Dominique; Yang, Fan

    2016-05-27

    Processing and analysis of Very High Resolution (VHR) satellite images provide a mass of crucial information, which can be used for urban planning, security issues or environmental monitoring. However, they are computationally expensive and, thus, time consuming, while some of the applications, such as natural disaster monitoring and prevention, require high efficiency performance. Fortunately, parallel computing techniques and embedded systems have made great progress in recent years, and a series of massively parallel image processing devices, such as digital signal processors or Field Programmable Gate Arrays (FPGAs), have been made available to engineers at a very convenient price and demonstrate significant advantages in terms of running-cost, embeddability, power consumption flexibility, etc. In this work, we designed a texture region segmentation method for very high resolution satellite images by using the level set algorithm and the multi-kernel theory in a high-abstraction C environment and realize its register-transfer level implementation with the help of a new proposed high-level synthesis-based design flow. The evaluation experiments demonstrate that the proposed design can produce high quality image segmentation with a significant running-cost advantage.

  13. Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms

    Directory of Open Access Journals (Sweden)

    Charlotte Bay Hasager

    2015-06-01

    Full Text Available Offshore wind farm cluster effects between neighboring wind farms increase rapidly with the large-scale deployment of offshore wind turbines. The wind farm wakes observed from Synthetic Aperture Radar (SAR are sometimes visible and atmospheric and wake models are here shown to convincingly reproduce the observed very long wind farm wakes. The present study mainly focuses on wind farm wake climatology based on Envisat ASAR. The available SAR data archive covering the large offshore wind farms at Horns Rev has been used for geo-located wind farm wake studies. However, the results are difficult to interpret due to mainly three issues: the limited number of samples per wind directional sector, the coastal wind speed gradient, and oceanic bathymetry effects in the SAR retrievals. A new methodology is developed and presented. This method overcomes effectively the first issue and in most cases, but not always, the second. In the new method all wind field maps are rotated such that the wind is always coming from the same relative direction. By applying the new method to the SAR wind maps, mesoscale and microscale model wake aggregated wind-fields results are compared. The SAR-based findings strongly support the model results at Horns Rev 1.

  14. Geo-Hazard Detection and Monitoring Using SAR and Optical Images in a Snow-Covered Area: The Menyuan (China Test Site

    Directory of Open Access Journals (Sweden)

    Qihuan Huang

    2017-09-01

    Full Text Available In this work, we combine SAR and optical images for geo-hazard detection and monitoring in Western China. An extremely small baseline of C-band SAR image pairs acquired from Sentinel-1A at Menyuan, China, is analyzed. Apart from the large area of coseismal deformation, we proposed an earthquake-derived landslide detecting method by removing the coseismal deformation with polynomial fitting, then the detected moving areas were confirmed with Chinese Gaofen-1 optical satellite images. Sentinel-1A C-band interferograms show about a 7-cm line of sight movement caused by the MS 6.4 Menyuan earthquake; meanwhile, several features indicative of ground movement were detected by the proposed method and demonstrated by the Gaofen-1 optical images; the interpretation of high-resolution optical data complemented the goal of better understanding the behavior of geo-hazard disasters. InSAR time series analysis provides an opportunity for continuous monitoring of geo-hazards in remote areas, while the optical image method is easily affected by decorrelation due to snowfall.

  15. System refinement for content based satellite image retrieval

    Directory of Open Access Journals (Sweden)

    NourElDin Laban

    2012-06-01

    Full Text Available We are witnessing a large increase in satellite generated data especially in the form of images. Hence intelligent processing of the huge amount of data received by dozens of earth observing satellites, with specific satellite image oriented approaches, presents itself as a pressing need. Content based satellite image retrieval (CBSIR approaches have mainly been driven so far by approaches dealing with traditional images. In this paper we introduce a novel approach that refines image retrieval process using the unique properties to satellite images. Our approach uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tiling sizes. Accordingly the system uses these multilevel features within a multilevel retrieval system that refines the retrieval process. Our multilevel refinement approach has been experimentally validated against the conventional one yielding enhanced precision and recall rates.

  16. ICA Based Speckle Filtering for Target Extraction in SAR Images Using Adaptive Space Separation

    Institute of Scientific and Technical Information of China (English)

    LI Yu-tong; ZHOU Yue; YANG Lei

    2008-01-01

    A novel approach based on independent component analysis (ICA) for speckle filtering and target extraction of synthetic aperture radar (SAR) images is proposed using adaptive space separation with weighted information entropy (WIE) incorporated. First the basis and the independent components are respectively obtained by ICA technique, and WIE of the image is computed; then based on the threshold computed from function T-WIE (threshold versus weighted-information-entropy), independent components are adaptively separated and the bases are classified accordingly. Thus, the image space is separated into two subspaces: "clean" and "noise". Then, a proposed nonlinear operator ABO is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.

  17. A NEW UNSUPERVISED CLASSIFICATION ALGORITHM FOR POLARIMETRIC SAR IMAGES BASED ON FUZZY SET THEORY

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Xie Yan; Pi Yiming; Hou Yinming

    2006-01-01

    In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combination of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classification accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by experiments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data.

  18. SAR image despeckling based on edge detection and nonsubsampled second generation bandelets

    Institute of Scientific and Technical Information of China (English)

    Zhang Wenge; Liu Fang; Jiao Licheng; Gao Xinbo

    2009-01-01

    To preserve the sharp features and details of the synthetic aperture radar (SAR) image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform (NSBT) domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges are detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Ganssian scale mixture (BLS-GSM).

  19. SAR image classification with non-stationary multinomial logistic mixture of amplitude and texture densities

    NARCIS (Netherlands)

    Kayabol, K.; Voisin, A.; Zerubia, J.

    2011-01-01

    We combine both amplitude and texture statistics of the Synthetic Aperture Radar (SAR) images using Products of Experts (PoE) approach for classification purpose. We use Nakagami density to model the class amplitudes. To model the textures of the classes, we exploit a non-Gaussian Markov Random Fiel

  20. Random Forests as a tool for estimating uncertainty at pixel-level in SAR image classification

    DEFF Research Database (Denmark)

    Loosvelt, Lien; Peters, Jan; Skriver, Henning

    2012-01-01

    , we introduce Random Forests for the probabilistic mapping of vegetation from high-dimensional remote sensing data and present a comprehensive methodology to assess and analyze classification uncertainty based on the local probabilities of class membership. We apply this method to SAR image data...... be easily assessed when using the Random Forests algorithm....

  1. A Novel Speckle Filter for SAR Images Based on Informationtheoretic Heterogeneity Measurements

    Institute of Scientific and Technical Information of China (English)

    Chen Jie; Zhu Jing; Li Chunsheng; Zhou Yinqing

    2009-01-01

    Most adaptive speckle filters are based on the local coefficient of variation, which serves to measure the heterogeneity of synthetic aperture radar (SAR) images. However, the sensitivity of the measurements to speckle and noise of SAR images would greatly deteriorate the speckle reduction. This article, based upon the information theory, presents a novel parameter for the heterogeneity measurement as a general index to quantitate the SAR image heterogeneity. Further, as a new speckle reduction algorithm based on the aforesaid quantitative heterogeneity measurements, it puts forward a heterogeneity-based speckle reduction filter (HBSRF), which uses the information-theoretic heterogeneity measurements as a criterion to classify the SAR images as belonging to homogeneous or heterogeneous regions. Then the finite iteration procedure and edge detection algorithms are adopted to strike the best balance between speckle reduction and edge preservation. The results from the computer simulation have demonstrated that the proposed effective method is superior to the conventional speckle filters based on the local coefficient of variation both in textural preservation and speckle reduction.

  2. GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    Catherine Mering

    2011-05-01

    Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

  3. SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

    Directory of Open Access Journals (Sweden)

    Wu Yiquan

    2017-08-01

    Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

  4. 14-bit pipeline-SAR ADC for image sensor readout circuits

    Science.gov (United States)

    Wang, Gengyun; Peng, Can; Liu, Tianzhao; Ma, Cheng; Ding, Ning; Chang, Yuchun

    2015-03-01

    A two stage 14bit pipeline-SAR analog-to-digital converter includes a 5.5bit zero-crossing MDAC and a 9bit asynchronous SAR ADC for image sensor readout circuits built in 0.18um CMOS process is described with low power dissipation as well as small chip area. In this design, we employ comparators instead of high gain and high bandwidth amplifier, which consumes as low as 20mW of power to achieve the sampling rate of 40MSps and 14bit resolution.

  5. A novel autofocus algorithm based on maximum total variation criteria for SAR images

    Institute of Scientific and Technical Information of China (English)

    MA Lun; LIAO Guisheng

    2007-01-01

    A novel autofocus algorithm for synthetic aperture radar (SAR)based on total variation is presented in this Paper.The method,which starts with a complex phase-degraded SAR image,after the phase errors model is introduced into the range-compressed phase-history domain,carries out phase errors correction by changing the focus till the total variation of the azimuth profile is maximized.Compared with the minimum entropy autofocus algorithm,the autofocus algorithm has less computational complexity and is easier to implement.The simulation and the processing results of the measured data show the validity of the proposed method.

  6. Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Vincent, Pauline; Badger, Jake

    2015-01-01

    Offshore wind farm cluster effects between neighboring wind farms increase rapidly with the large-scale deployment of offshore wind turbines. The wind farm wakes observed from Synthetic Aperture Radar (SAR) are sometimes visible and atmospheric and wake models are here shown to convincingly...... to interpret due to mainly three issues: the limited number of samples per wind directional sector, the coastal wind speed gradient, and oceanic bathymetry effects in the SAR retrievals. A new methodology is developed and presented. This method overcomes effectively the first issue and in most cases...

  7. Semi-supervised Learning for Classification of Polarimetric SAR Images Based on SVM-Wishart

    Directory of Open Access Journals (Sweden)

    Hua Wen-qiang

    2015-02-01

    Full Text Available In this study, we propose a new semi-supervised classification method for Polarimetric SAR (PolSAR images, aiming at handling the issue that the number of train set is small. First, considering the scattering characters of PolSAR data, this method extracts multiple scattering features using target decomposition approach. Then, a semi-supervised learning model is established based on a co-training framework and Support Vector Machine (SVM. Both labeled and unlabeled data are utilized in this model to obtain high classification accuracy. Third, a recovery scheme based on the Wishart classifier is proposed to improve the classification performance. From the experiments conducted in this study, it is evident that the proposed method performs more effectively compared with other traditional methods when the number of train set is small.

  8. PSI Deformation Map Retrieval by Means of Temporal Sublook Coherence on Reduced Sets of SAR Images

    Directory of Open Access Journals (Sweden)

    Rubén Iglesias

    2015-01-01

    Full Text Available Prior to the application of any persistent scatterer interferometry (PSI technique for the monitoring of terrain displacement phenomena, an adequate pixel selection must be carried out in order to prevent the inclusion of noisy pixels in the processing. The rationale is to detect the so-called persistent scatterers, which are characterized by preserving their phase quality along the multi-temporal set of synthetic aperture radar (SAR images available. Two criteria are mainly available for the estimation of pixels’ phase quality, i.e., the coherence stability and the amplitude dispersion or permanent scatterers (PS approach. The coherence stability method allows an accurate estimation of the phase statistics, even when a reduced number of SAR acquisitions is available. Unfortunately, it requires the multi-looking of data during the coherence estimation, leading to a spatial resolution loss in the final results. In contrast, the PS approach works at full-resolution, but it demands a larger number of SAR images to be reliable, typically more than 20. There is hence a clear limitation when a full-resolution PSI processing is to be carried out and the number of acquisitions available is small. In this context, a novel pixel selection method based on exploiting the spectral properties of point-like scatterers, referred to as temporal sublook coherence (TSC, has been recently proposed. This paper seeks to demonstrate the advantages of employing PSI techniques by means of TSC on both orbital and ground-based SAR (GB-SAR data when the number of images available is small (10 images in the work presented. The displacement maps retrieved through the proposed technique are compared, in terms of pixel density and phase quality, with traditional criteria. Two X-band datasets composed of 10 sliding spotlight TerraSAR-X images and 10 GB-SAR images, respectively, over the landslide of El Forn de Canillo (Andorran Pyrenees, are employed for this study. For both

  9. MODIS 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  10. ASTER 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  11. AUTOMATIC SHIP DETECTION IN SINGLE-POL SAR IMAGES USING TEXTURE FEATURES IN ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    E. Khesali

    2015-12-01

    Full Text Available This paper presents a novel method for detecting ships from high-resolution synthetic aperture radar (SAR images. This method categorizes ship targets from single-pol SAR images using texture features in artificial neural networks. As such, the method tries to overcome the lack of an operational solution that is able to reliably detect ships with one SAR channel. The method has the following three main stages: 1 feature extraction; 2 feature selection; and 3 ship detection. The first part extracts different texture features from SAR image. These textures include occurrence and co occurrence measures with different window sizes. Then, best features are selected. Finally, the artificial neural network is used to extract ship pixels from sea ones. In post processing stage some morphological filters are used to improve the result. The effectiveness of the proposed method is verified using Sentinel-1 data in VV polarization. Experimental results indicate that the proposed algorithm can be implemented with time-saving, high precision ship extraction, feature analysis, and detection. The results also show that using texture features the algorithm properly discriminates speckle noise from ships.

  12. IMAGING AND MTI PROCESSING BASED ON DUAL-FREQUENCIES DUAL-APERTURES SPACEBORNE SAR

    Institute of Scientific and Technical Information of China (English)

    Yin Jianfeng; Li Daojing; Wu Yirong

    2009-01-01

    Based on dual-frequencies dual-apertures spaceborne SAR (Synthetic Aperture Radar), a new SAR system with four receiving channels and two operation modes is presented in this paper. SAR imaging and Moving Target Indication (MTI) are studied in this system. High resolution imaging with wide swath is implemented by the Mode I, and MTI is completed by the Mode II. High azimuth resolution is achieved by the Displaced Phase Center (DPC) multibeam technique. And the Coherent Accumulation (CA) method, which combines dual channels data of different carrier frequency, is used to enhance the range resolution. For the data of different carrier frequency, the two aperture interferometric processing is executed to implement clutter cancellation, respectively. And the couple of clutter suppressed data are employed to implement Dual Carrier Frequency Conjugate Processing (DCFCP), then both slow and fast moving targets detection can be completed, followed by moving target imaging. The simulation results show the validity of the signal processing method of this new SAR system.

  13. An efficient two-objective automatic SAR image segmentation framework using artificial immune system

    Science.gov (United States)

    Yang, Dongdong; Niu, Ruican; Fei, Rong; Jiang, Qiaoyong; Li, Hongye; Cao, Zijian

    2015-12-01

    Here, an efficient multi-objective automatic segmentation framework (MASF) is formulated and applied to synthetic aperture radar (SAR) image unsupervised classification. In the framework, three important issues are presented: 1) two reasonable image preprocessing techniques, including spatial filtering and watershed operator, are discussed at the initial stage of the framework; 2)then, an efficient immune multi-objective optimization algorithm with uniform clone, adaptive selection by online nondominated solutions, and dynamic deletion in diversity maintenance is proposed; 3 two very simple, but very efficient conflicting clustering validity indices are incorporated into the framework and simultaneously optimized. Two simulated SAR data and two complicated real images are used to quantitatively validate its effectiveness. In addition, four other state-of-the-art image segmentation methods are employed for comparison.

  14. Discernibility of Burial Mounds in High-Resolution X-Band SAR Images for Archaeological Prospections in the Altai Mountains

    Directory of Open Access Journals (Sweden)

    Timo Balz

    2016-09-01

    Full Text Available The Altai Mountains are a heritage-rich archaeological landscape with monuments in almost every valley. Modern nation state borders dissect the region and limit archaeological landscape analysis to intra-national areas of interest. Remote sensing can help to overcome these limitations. Due to its high precision, Synthetic Aperture Radar (SAR data can be a very useful tool for supporting archaeological prospections, but compared to optical imagery, the detectability of sites of archaeological interest is limited. We analyzed the limitations of SAR using TerraSAR-X images in different modes. Based on ground truth, the discernibility of burial mounds was analyzed in different SAR acquisition modes. We show that very-high-resolution TerraSAR-X staring spotlight images are very well suited for the task, with >75% of the larger mounds being discernible, while in images with a lower spatial resolution only a few large sites can be detected, at rates below 50%.

  15. Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

    Directory of Open Access Journals (Sweden)

    Osmar Abílio de Carvalho Júnior

    2014-04-01

    Full Text Available Speckle noise (salt and pepper is inherent to synthetic aperture radar (SAR, which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA, a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS Phased-Array Synthetic-Aperture Radar (PALSAR sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari, containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF or noise-adjusted principal components (NAPCs. Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

  16. In situ validation of segmented SAR satellite scenes of young Arctic thin landfast sea ice

    Science.gov (United States)

    Gerland, S.; Negrel, J.; Doulgeris, A. P.; Akbari, V.; Lauknes, T. R.; Rouyet, L.; Storvold, R.

    2016-12-01

    The use of satellite remote sensing techniques for the observation and monitoring of the polar regions has increased in recent years due to the ability to cover larger areas than can be covered by ground measurements, However, in situ data remain mandatory for the validation of such data. In April 2016 an Arctic fieldwork campaign was conducted at Kongsfjorden, Svalbard. Ground measurements from this campaign are used together with satellite data acquisitions to improve identification of young sea ice types from satellite data. This work was carried out in combination with Norwegian Polar Institute's long-term monitoring of Svalbard fast ice, and with partner institutes in the Center for Integrated Remote Sensing and Forecasting for Arctic operations (CIRFA). Thin ice types are generally more difficult to investigate than thicker ice, because ice of only a few centimetres thickness does not allow scientists to stand and work on it. Identifying it on radar scenes will make it easier to study and monitor. Four high resolution 25 km x 25 km Radarsat-2 quad-pol scenes were obtained, coincident in space and time with the in situ measurements. The field teams used a variety of methods, including ice thickness transects, ice salinity measurements, ground-based radar imaging from the coast and UAV-based photography, to identify the different thin ice types, their location and evolution in time. Sampling of the thinnest ice types was managed from a small boat. In addition, iceberg positions were recorded with GPS and photographed to enable us to quantify their contribution to the radar response. Thin ice from 0.02 to 0.18 m thickness was sampled on in a total nine ice stations. The ice had no or only a thin snow layer. The GPS positions and tracks and ice characteristics are then compared to the Radarsat-2 scenes, and the radar responses of the different thin ice types in the quad-pol scenes are identified. The first segmentation results of the scenes present a good

  17. Polar-Orbiting Satellite (POES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...

  18. EXTRACTION OF COASTLINES WITH FUZZY APPROACH USING SENTINEL-1 SAR IMAGE

    Directory of Open Access Journals (Sweden)

    N. Demir

    2016-06-01

    Full Text Available Coastlines are important features for water resources, sea products, energy resources etc. Coastlines are changed dynamically, thus automated methods are necessary for analysing and detecting the changes along the coastlines. In this study, Sentinel-1 C band SAR image has been used to extract the coastline with fuzzy logic approach. The used SAR image has VH polarisation and 10x10m. spatial resolution, covers 57 sqkm area from the south-east of Puerto-Rico. Additionally, radiometric calibration is applied to reduce atmospheric and orbit error, and speckle filter is used to reduce the noise. Then the image is terrain-corrected using SRTM digital surface model. Classification of SAR image is a challenging task since SAR and optical sensors have very different properties. Even between different bands of the SAR sensors, the images look very different. So, the classification of SAR image is difficult with the traditional unsupervised methods. In this study, a fuzzy approach has been applied to distinguish the coastal pixels than the land surface pixels. The standard deviation and the mean, median values are calculated to use as parameters in fuzzy approach. The Mean-standard-deviation (MS Large membership function is used because the large amounts of land and ocean pixels dominate the SAR image with large mean and standard deviation values. The pixel values are multiplied with 1000 to easify the calculations. The mean is calculated as 23 and the standard deviation is calculated as 12 for the whole image. The multiplier parameters are selected as a: 0.58, b: 0.05 to maximize the land surface membership. The result is evaluated using airborne LIDAR data, only for the areas where LIDAR dataset is available and secondly manually digitized coastline. The laser points which are below 0,5 m are classified as the ocean points. The 3D alpha-shapes algorithm is used to detect the coastline points from LIDAR data. Minimum distances are calculated between the

  19. AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

  20. Automatic Approach to Vhr Satellite Image Classification

    Science.gov (United States)

    Kupidura, P.; Osińska-Skotak, K.; Pluto-Kossakowska, J.

    2016-06-01

    In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture), which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the preliminary step

  1. Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis

    Science.gov (United States)

    Lee, Isabella K.; Shamsoddini, Ali; Li, Xiaofeng; Trinder, John C.; Li, Zeyu

    2016-07-01

    Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. A morphology-based analyses of the subsequent reconstructions of the hurricane eyes shows a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.

  2. Synthetic aperture integration (SAI) algorithm for SAR imaging

    Science.gov (United States)

    Chambers, David H; Mast, Jeffrey E; Paglieroni, David W; Beer, N. Reginald

    2013-07-09

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  3. MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

    Energy Technology Data Exchange (ETDEWEB)

    Eichel, Paul H.

    2013-08-01

    MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.

  4. Straight Line Extraction by Heuristic Search for SAR Image%SAR 图像启发式搜索直线提取

    Institute of Scientific and Technical Information of China (English)

    曾阳帆; 刘伟; 陈建宏; 赵拥军

    2015-01-01

    Straight line feature is the basis of linear target recognition.The existing heuristic search algorithms are suit-able for straight line feature extraction in optical image while performing poor in SAR image.For this problem,a straight line extraction method for SAR image based on heuristic search is presented.Firstly,SAR image is filtered by Frost filter. Then,edges are detected by ratio of exponential weighted average (ROEWA)operator and non-maxima suppression location algorithm is adopted to obtain the binary edge map.Finally,considering the local information sufficiently,the strategy of search twice and the principle of “go straight”is utilized and the cost function and rules of heuristic search are designed. Then the straight line extraction is completed.The experiment results show good anti-noise performance and fracture resist-ance of the proposed method which can effectively describe the straight line feature of SAR images.%直线特征是识别线状目标的基础,现有启发式搜索算法仅适用于光学图像的直线特征提取,对 SAR 图像效果并不理想。针对该问题,提出一种 SAR 图像直线特征提取的启发式搜索算法。首先对 SAR 图像进行 Frost滤波,然后利用指数加权均值比(ROEWA)算子进行边缘检测,再利用非极值抑制得到边缘二值图,最后采用二次搜索策略及“直线走原则”,充分考虑局部信息,设计启发式搜索的代价函数及搜索规则,实现直线特征提取。实验结果表明,该方法具有较好的抗噪性和抗断裂能力,能够有效地提取出 SAR 图像中的直线特征。

  5. Contextual descriptors and neural networks for scene analysis in VHR SAR images

    Science.gov (United States)

    Del Frate, Fabio; Picchiani, Matteo; Falasco, Alessia; Schiavon, Giovanni

    2016-10-01

    The development of SAR technology during the last decade has made it possible to collect a huge amount of data over many regions of the world. In particular, the availability of SAR images from different sensors, with metric or sub-metric spatial resolution, offers novel opportunities in different fields as land cover, urban monitoring, soil consumption etc. On the other hand, automatic approaches become crucial for the exploitation of such a huge amount of information. In such a scenario, especially if single polarization images are considered, the main issue is to select appropriate contextual descriptors, since the backscattering coefficient of a single pixel may not be sufficient to classify an object on the scene. In this paper a comparison among three different approaches for contextual features definition is presented so as to design optimum procedures for VHR SAR scene understanding. The first approach is based on Gray Level Co- Occurrence Matrix since it is widely accepted and several studies have used it for land cover classification with SAR data. The second approach is based on the Fourier spectra and it has been already proposed with positive results for this kind of problems, the third one is based on Auto-associative Neural Networks which have been already proven effective for features extraction from polarimetric SAR images. The three methods are evaluated in terms of the accuracy of the classified scene when the features extracted using each method are considered as input to a neural network classificator and applied on different Cosmo-SkyMed spotlight products.

  6. Doppler Spectrum-Based NRCS Estimation Method for Low-Scattering Areas in Ocean SAR Images

    Directory of Open Access Journals (Sweden)

    Hui Meng

    2017-02-01

    Full Text Available The image intensities of low-backscattering areas in synthetic aperture radar (SAR images are often seriously contaminated by the system noise floor and azimuthal ambiguity signal from adjacent high-backscattering areas. Hence, the image intensity of low-backscattering areas does not correctly reflect the backscattering intensity, which causes confusion in subsequent image processing or interpretation. In this paper, a method is proposed to estimate the normalized radar cross-section (NRCS of low-backscattering area by utilizing the differences between noise, azimuthal ambiguity, and signal in the Doppler frequency domain of single-look SAR images; the aim is to eliminate the effect of system noise and azimuthal ambiguity. Analysis shows that, for a spaceborne SAR with a noise equivalent sigma zero (NESZ of −25 dB and a single-look pixel of 8 m × 5 m, the NRCS-estimation precision of this method can reach −38 dB at a resolution of 96 m × 100 m. Three examples are given to validate the advantages of this method in estimating the low NRCS and the filtering of the azimuthal ambiguity.

  7. A SIFT Algorithm for Bistatic SAR Imaging in a Spaceborne Constant-offset Configuration (in English

    Directory of Open Access Journals (Sweden)

    Chen Shi-chao

    2013-03-01

    Full Text Available This paper focuses on the problem of the space-variance of the range-cell migration term for bistatic Synthetic Aperture Radar (SAR and proposes a Scaled Inverse Fourier Transform (SIFT-based imaging algorithm for the constant-offset configuration of bistatic SAR data processing. Range-cell migration correction is realized when two times phase multiplies and a convolution operation are executed. Because the imaging algorithm is based on a precise spectrum that has been deduced from the Geometry-Based Formula (GBF algorithm, the proposed algorithm can handle the bistatic SAR data, which were obtained with a large baseline to ratio. The advantages and effectiveness of the proposed imaging method have been verified by simulated and comparable experiments. Moreover, unlike other scaling-imaging algorithms that are dependent on the frequency modulated characteristics of the signal, the SIFT imaging algorithm is also suitable for phase-coded signals, which are used in a wider range of applications.

  8. High-resolution real-time imaging processor for airborne SAR

    Science.gov (United States)

    Yu, Weidong; Wu, Shumei

    2003-04-01

    Real-time imaging processor can provide Synthetic Aperture Radar (SAR) image in real-time mode, which is necessary for airborne SAR applications such as real-time monitoring and battle reconnaissance. This paper describes the development of high-resolution real-time imaging processor in Institute of Electronic, Chinese Academy of Sciences (IECAS). The processor uses parallel multiple channels to implement large-volume calculation needed for SAR real-time imaging. A sub-aperture method is utilized to divide azimuth Doppler spectrum into two parts, which correspond two looks. With sub-aperture method, high processing efficiency, less range migration effect and reduced memory volume can be achieved. The imaging swath is also divided into two segments, which are processed in a parallel way. Range-Doppler algorithm, which consists of range migration correction and azimuth compression, is implemented in the processor. Elaborate software programming ensures a high efficient utilization of hardware. Experimental simulation and field flight indicate this system is successful. The principles, architecture, hardware implementation of the processor are presented in this paper in details.

  9. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Science.gov (United States)

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  10. Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

    Science.gov (United States)

    Marghany, Maged

    2016-10-01

    In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

  11. Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Marghany Maged

    2016-10-01

    Full Text Available In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiver-operating characteristic (ROC curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

  12. Error Modeling and Analysis for InSAR Spatial Baseline Determination of Satellite Formation Flying

    Directory of Open Access Journals (Sweden)

    Jia Tu

    2012-01-01

    Full Text Available Spatial baseline determination is a key technology for interferometric synthetic aperture radar (InSAR missions. Based on the intersatellite baseline measurement using dual-frequency GPS, errors induced by InSAR spatial baseline measurement are studied in detail. The classifications and characters of errors are analyzed, and models for errors are set up. The simulations of single factor and total error sources are selected to evaluate the impacts of errors on spatial baseline measurement. Single factor simulations are used to analyze the impact of the error of a single type, while total error sources simulations are used to analyze the impacts of error sources induced by GPS measurement, baseline transformation, and the entire spatial baseline measurement, respectively. Simulation results show that errors related to GPS measurement are the main error sources for the spatial baseline determination, and carrier phase noise of GPS observation and fixing error of GPS receiver antenna are main factors of errors related to GPS measurement. In addition, according to the error values listed in this paper, 1 mm level InSAR spatial baseline determination should be realized.

  13. GEO-LEO BI-SAR imaging algorithm%GEO-LEO双基地SAR成像算法研究

    Institute of Scientific and Technical Information of China (English)

    董众; 徐卓异; 张善从

    2014-01-01

    A Doppler distribution weighted method is proposed to solve the two-dimensional spectrum of GEO-LEO Bi-SAR imaging system. Different from the existing methods,this method deduces the corresponding analytical expression according to the physical significance of weight factor and the orbital parameters of GEO-LEO satellites. The solution difficulty of the two-di-mensional spectrum expression was overcome without any introducing errors. In combination with an Inverse Scaled Fast Fourier Transformation algorithm,the accurate ground target imaging of GEO-LEO Bi-SAR was realized. The simulation results show the advantages of the imaging method proposed in the paper.%提出一种基于多普勒贡献比加权的GEO-LEO星载双基地SAR二维频谱求解方法,与现有的频谱求解方法不同,该方法根据加权因子的物理意义,并利用GEO-LEO的轨道参数推导其相应的解析表达式,在没有引入误差的情况下,解决了GEO-LEO双基地SAR的二维频谱表达式求解问题。并与二维尺度变换逆FFT成像算法结合,实现了GEO-LEO双基地SAR对地面目标的精确成像。仿真实验结果表明了算法的优越性。

  14. Using SAR and GPS for Hazard Management and Response: Progress and Examples from the Advanced Rapid Imaging and Analysis (ARIA) Project

    Science.gov (United States)

    Owen, S. E.; Simons, M.; Hua, H.; Yun, S. H.; Agram, P. S.; Milillo, P.; Sacco, G. F.; Webb, F.; Rosen, P. A.; Lundgren, P.; Milillo, G.; Manipon, G. J. M.; Moore, A. W.; Liu, Z.; Polet, J.; Cruz, J.

    2014-12-01

    ARIA is a joint JPL/Caltech project to automate synthetic aperture radar (SAR) and GPS imaging capabilities for scientific understanding, hazard response, and societal benefit. We have built a prototype SAR and GPS data system that forms the foundation for hazard monitoring and response capability, as well as providing imaging capabilities important for science studies. Together, InSAR and GPS have the ability to capture surface deformation in high spatial and temporal resolution. For earthquakes, this deformation provides information that is complementary to seismic data on location, geometry and magnitude of earthquakes. Accurate location information is critical for understanding the regions affected by damaging shaking. Regular surface deformation measurements from SAR and GPS are useful for monitoring changes related to many processes that are important for hazard and resource management such as volcanic deformation, groundwater withdrawal, and landsliding. Observations of SAR coherence change have a demonstrated use for damage assessment for hazards such as earthquakes, tsunamis, hurricanes, and volcanic eruptions. These damage assessment maps can be made from imagery taken day or night and are not affected by clouds, making them valuable complements to optical imagery. The coherence change caused by the damage from hazards (building collapse, flooding, ash fall) is also detectable with intelligent algorithms, allowing for rapid generation of damage assessment maps over large areas at fine resolution, down to the spatial scale of single family homes. We will present the progress and results we have made on automating the analysis of SAR data for hazard monitoring and response using data from the Italian Space Agency's (ASI) COSMO-SkyMed constellation of X-band SAR satellites. Since the beginning of our project with ASI, our team has imaged deformation and coherence change caused by many natural hazard events around the world. We will present progress on our

  15. NOVEL APPROACH BASED ON DERAMPING TECHNIQUE FOR SQUINTED SLIDING SPOTLIGHT SAR IMAGING

    Institute of Scientific and Technical Information of China (English)

    Mo Yajun; Yan He; Zhao Bingji

    2013-01-01

    This paper investigates a novel approach based on the deramping technique for squinted sliding spotlight Synthetic Aperture Radar (SAR) imaging to resolve the azimuth spectrum aliasing problem.First of all,the properties of the azimuth spectrum and the squint angle impacts on the azimuth spectrum aliasing problem are analyzed.Based on the analysis result,an operation of filtering is added to the azimuth preprocessing step of traditional Two-Step Focusing Approach (TSPA) to resolve the azimuth folding problem and remove the influence of the squint angle on the azimuth spectrum aliasing problem.Then,a modified Range Migration Algorithm (RMA) is performed to obtain the precise focused image.Furthermore,the focused SAR image folding problem of traditional TSPA is illuminated in this paper.An azimuth post-processing step is proposed to unfold the aliased SAR image.Simulation experiment results prove that the proposed approach can solve the spectrum aliasing problem and process squinted sliding spotlight data efficiently.

  16. SAR Image Segmentation with Unknown Number of Classes Combined Voronoi Tessellation and Rjmcmc Algorithm

    Science.gov (United States)

    Zhao, Q. H.; Li, Y.; Wang, Y.

    2016-06-01

    This paper presents a novel segmentation method for automatically determining the number of classes in Synthetic Aperture Radar (SAR) images by combining Voronoi tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC) strategy. Instead of giving the number of classes a priori, it is considered as a random variable and subject to a Poisson distribution. Based on Voronoi tessellation, the image is divided into homogeneous polygons. By Bayesian paradigm, a posterior distribution which characterizes the segmentation and model parameters conditional on a given SAR image can be obtained up to a normalizing constant; Then, a Revisable Jump Markov Chain Monte Carlo(RJMCMC) algorithm involving six move types is designed to simulate the posterior distribution, the move types including: splitting or merging real classes, updating parameter vector, updating label field, moving positions of generating points, birth or death of generating points and birth or death of an empty class. Experimental results with real and simulated SAR images demonstrate that the proposed method can determine the number of classes automatically and segment homogeneous regions well.

  17. SAR Ice Image Classification Using Parallelepiped Classifier Based on Gram-Schmidt Spectral Technique

    Directory of Open Access Journals (Sweden)

    A.Vanitha

    2013-05-01

    Full Text Available Synthetic Aperture Radar (SAR is a special type of imaging radar that involves advanced technology and complex data processing to obtain de tailed images from the lake surface. Lake ice typically reflects more of the radar energy emi tted by the sensor than the surrounding area, which makes it easy to distinguish between the wate r and the ice surface. In this research work, SAR images are used for ice classification based on supervised and unsupervised classification algorithms. In the pre-processing stage, Hue satura tion value (HSV and Gram–Schmidt spectral sharpening techniques are applied for shar pening and resampling to attain high- resolution pixel size. Based on the performance eva luation metrics it is proved that Gram- Schmidt spectral sharpening performs better than sh arpening the HSV between the boundaries. In classification stage, Gram–Schmidt spectral tech nique based sharpened SAR images are used as the input for classifying using parallelepiped a nd ISO data classifier. The performances of the classifiers are evaluated with overall accuracy and kappa coefficient. From the experimental results, ice from water is classified more accurately in the parallelepiped supervised classification algorithm.

  18. Integrated Shoreline Extraction Approach with Use of Rasat MS and SENTINEL-1A SAR Images

    Science.gov (United States)

    Demir, N.; Oy, S.; Erdem, F.; Şeker, D. Z.; Bayram, B.

    2017-09-01

    Shorelines are complex ecosystems and highly important socio-economic environments. They may change rapidly due to both natural and human-induced effects. Determination of movements along the shoreline and monitoring of the changes are essential for coastline management, modeling of sediment transportation and decision support systems. Remote sensing provides an opportunity to obtain rapid, up-to-date and reliable information for monitoring of shoreline. In this study, approximately 120 km of Antalya-Kemer shoreline which is under the threat of erosion, deposition, increasing of inhabitants and urbanization and touristic hotels, has been selected as the study area. In the study, RASAT pansharpened and SENTINEL-1A SAR images have been used to implement proposed shoreline extraction methods. The main motivation of this study is to combine the land/water body segmentation results of both RASAT MS and SENTINEL-1A SAR images to improve the quality of the results. The initial land/water body segmentation has been obtained using RASAT image by means of Random Forest classification method. This result has been used as training data set to define fuzzy parameters for shoreline extraction from SENTINEL-1A SAR image. Obtained results have been compared with the manually digitized shoreline. The accuracy assessment has been performed by calculating perpendicular distances between reference data and extracted shoreline by proposed method. As a result, the mean difference has been calculated around 1 pixel.

  19. Significant wave height estimation using azimuth cutoff of C-band RADARSAT-2 single-polarization SAR images

    Institute of Scientific and Technical Information of China (English)

    REN Lin; YANG Jingsong; ZHENG Gang; WANG Juan

    2015-01-01

    This paper proposes two simple models, look-up table (LUT) model and empirical model, to directly retrieve significant wave height (Hs) using synthetic aperture radar (SAR) azimuth cutoff (λc). Both models aim at C-band VV, HH, VH, and HV single-polarization SAR images. The LUT model relatesHs toλc, while the empirical model relatesHs to bothλc and SAR range-to-velocity (β). The LUT model coefficients are derived by simulation under different sea states and observation conditions, which depend on incidence angle (θ), wave direction (dw), andβbut are independent of polarization. The empirical model coefficients are obtained by fitting the collocated data, which only depend on polarization. To fit empirical model coefficients and validate the two models, C-band RADARSAT-2 fine quad-polarization (VV+HH+VH+HV) single-look complex (SLC) SAR images and collocated buoy data are collected. RetrievedHs, using Yang model and the two models proposed in this paper from four kinds of polarization SAR data, are compared with buoyHs. Results show that both LUT and empirical models have the capacity of retrievingHs from C-band RADARSAT-2 co-polarization SAR data, while Yang model is not suitable for these kinds of SAR data. Moreover, the empirical model is also valid for cross-polarization SAR data showing clear ocean wave stripes.

  20. Speckle reduction of SAR images using ICA basis enhancement and separation

    Institute of Scientific and Technical Information of China (English)

    Yutong Li; Yue zhou

    2007-01-01

    @@ An approach for synthetic aperture radax (SAR) image de-noising based on independent component analysis (ICA) basis images is proposed. Firstly, the basis images and the code matrix of the original image are obtained using ICA algorithm. Then, pointwise H(o)lder exponent of each basis is computed as a cost criterion for basis enhancement, and then the enhanced basis images are classified into two sets according to a separation rule which separates the clean basis from the original basis. After these key procedures for speckle reduction, the clean image is finally obtained by reconstruction on the clean basis and original code matrix. The reconstructed image shows better visual perception and image quality compared with those obtained by other traditional techniques.

  1. On the Effects of Imaging Geometry on Multipolarization SAR Features for Oil Spill Observation

    Science.gov (United States)

    Skrunes, Stine; Jones, Cathleen E.; Brekke, Camilla; Holt, Benjamin; Espeseth, Martine M.

    2016-08-01

    Polarimetric SAR is increasingly used for oil spill observation. In order to develop reliable methods for oil spill detection and characterization, the sensitivity of these measurements to the imaging geometry, including incidence angle and look direction relative to the wind, must be investigated. In this paper, we study the effects of these parameters on L-band SAR data collected with the UAVSAR instrument over experimental oil spills. The relative look direction is found to have a larger effect on the slick detectability than the incidence angle, and the detectability is better in the downwind direction compared to upwind. The features showing the best slick detectability in the conditions investigated here are the VV intensity, HV intensity, the geometric intensity and the polarization difference. The latter feature shows low dependency on imaging geometry.

  2. Two-dimensional Fast ESPRIT Algorithm for Linear Array SAR Imaging

    Directory of Open Access Journals (Sweden)

    Zhao Yi-chao

    2015-10-01

    Full Text Available The linear array Synthetic Aperture Radar (SAR system is a popular research tool, because it can realize three-dimensional imaging. However, owning to limitations of the aircraft platform and actual conditions, resolution improvement is difficult in cross-track and along-track directions. In this study, a twodimensional fast Estimation of Signal Parameters by Rotational Invariance Technique (ESPRIT algorithm for linear array SAR imaging is proposed to overcome these limitations. This approach combines the Gerschgorin disks method and the ESPRIT algorithm to estimate the positions of scatterers in cross and along-rack directions. Moreover, the reflectivity of scatterers is obtained by a modified pairing method based on “region growing”, replacing the least-squares method. The simulation results demonstrate the applicability of the algorithm with high resolution, quick calculation, and good real-time response.

  3. Enhancement of SAR Ship Wake Image Based on FABEMD and Goldstein Filter

    Directory of Open Access Journals (Sweden)

    Zhang Wen-yi

    2012-12-01

    Full Text Available Enhanced SAR ship wake images with blur Kelvin wakes and reserved turbulent wakes are very important to the inversions of ship and motion parameters. This paper applies the Fast and Adaptive Bidimensional Empirical Mode Decomposition (FABEMD to decompose the SAR ship wake image into Kelvin wakes, turbulent wakes and other multiscale features, which enhances the gray intensity and spectrum contrast of Kelvin wakes to other features. Based on the FABEMD, a modified Goldstein interferogram filter is developed to further enhance the Kelvin wakes. Moreover, the moment invariants are introduced to evaluate the enhancement. Therefore, the Kelvin wakes are dramatically enhanced and the turbulent wakes are reserved. Algorithm analysis, experiments, subjective and objective evaluations show the reasonable efficiency and capabilities.

  4. Classification of PolSAR image based on quotient space theory

    Science.gov (United States)

    An, Zhihui; Yu, Jie; Liu, Xiaomeng; Liu, Limin; Jiao, Shuai; Zhu, Teng; Wang, Shaohua

    2015-12-01

    In order to improve the classification accuracy, quotient space theory was applied in the classification of polarimetric SAR (PolSAR) image. Firstly, Yamaguchi decomposition method is adopted, which can get the polarimetric characteristic of the image. At the same time, Gray level Co-occurrence Matrix (GLCM) and Gabor wavelet are used to get texture feature, respectively. Secondly, combined with texture feature and polarimetric characteristic, Support Vector Machine (SVM) classifier is used for initial classification to establish different granularity spaces. Finally, according to the quotient space granularity synthetic theory, we merge and reason the different quotient spaces to get the comprehensive classification result. Method proposed in this paper is tested with L-band AIRSAR of San Francisco bay. The result shows that the comprehensive classification result based on the theory of quotient space is superior to the classification result of single granularity space.

  5. Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

    Science.gov (United States)

    Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

    2015-01-01

    This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

  6. MAXIMUM A POSTERIORI-BASED AUTOMATIC TARGET DETECTION IN SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    Wang Yimin; An Jinwen

    2005-01-01

    The paper presents an algorithm of automatic target detection in Synthetic Aperture Radar(SAR) images based on Maximum A Posteriori(MAP). The algorithm is divided into three steps. First, it employs Gaussian mixture distribution to approximate and estimate multi-modal histogram of SAR image. Then, based on the principle of MAP, when a priori probability is both unknown and learned respectively, the sample pixels are classified into different classes c = {target,shadow, background}. Last, it compares the results of two different target detections. Simulation results preferably indicate that the presented algorithm is fast and robust, with the learned a priori probability, an approach to target detection is reliable and promising.

  7. Change Detection of High Resolution SAR Images by the Fusion of Coherent/Incoherent Information

    Directory of Open Access Journals (Sweden)

    Yang Xiang-li

    2015-10-01

    Full Text Available Aiming at detecting the change regions of high resolution Synthetic Aperture Radar (SAR images, we propose to use the Dempster-Shafer (D-S evidence theory to fuse coherent/incoherent features from sensors that form an integral part of the system. First, we use the Simple Linear Iterative Clustering (SLIC segmentation algorithm to implement multi-scale joint segmentation for multi-temporal SAR images. Second, we extract multiple intensity and coherence difference features on each segment level by SLIC using mean operator to complete the fusion of multi-scale features to get the multi-feature difference mapped by a ratio operator. Finally, we fuse the multi-feature difference maps to get the final change detection result using the D-S evidence theory. The experimental results in our study prove the effectiveness of our proposed computational algorithm.

  8. Accuracy comparison of Pléiades satellite ortho-images using GPS ...

    African Journals Online (AJOL)

    Ivan Henrico

    a new and improved dimension to the pointing accuracies of current and future .... It is stated in the TerraSAR-X GCP-3 Coordinate Specification and Accuracy .... parameters for camera timing, alignment, focal plane and satellites altitude.

  9. Quantization analysis of the real-time SAR digital image formation processor

    Energy Technology Data Exchange (ETDEWEB)

    Magotra, N.

    1988-12-01

    This report presents a quantization analysis of the digital image formation processor (IFP) of a linear-FM synthetic aperture radar (SAR). The IFP is configured as a patch processor and forms the final image by performing a two dimensional Fast Fourier Transform (FFT). The quantization analysis examines the effects of using fixed precision arithmetic in the image formation process. Theoretical bounds for the worst-case errors introduced by using fixed point arithmetic and experimental results verifying the theoretical bounds are presented. 34 refs., 23 figs., 7 tabs.

  10. Satellite SAR imagery for site discovery, change detection and monitoring activities in cultural heritage sites : experiments on the Nasca region, Peru

    OpenAIRE

    Tapete, D.; Cigna, F.; N. Masini; Lasaponara, R.

    2012-01-01

    Besides their suitability for multi-temporal and spatial deformation analysis, the Synthetic Aperture Radar (SAR) image archives acquired by space-borne radar sensors can be exploited to support archaeological investigations over huge sites, even those partially or totally buried and still to be excavated. Amplitude information is one of the main properties of SAR data from which it is possible to retrieve evidences of buried structures, using feature extraction and texture analysis. Multi-te...

  11. Edge Detection of PolSAR Image Based on Stochastic Distance

    OpenAIRE

    Wang, Qing; ZENG Qiming; Zhang, Haizhen; JIAO Jian

    2015-01-01

    A new edge detection methodology in PolSAR images is proposed, which is based on stochastic distance in the statistical theory and combined with complex Wishart distribution. Its main principle is inspired from the phenomenon that stochastic distance of two classes separated by an edge is closely related to the edge direction and the contrast of two classes. Simulation experiments are carried out to analyze the performance of the proposed methods. Results prove that methods have better capabi...

  12. "Phase-Enhanced" 3D Snapshot ISAR Imaging and Interferometric SAR

    Science.gov (United States)

    2009-12-28

    contained in the two nearly identical in amplitude data sets. References [5-7] provide a good discussion of the basic principles and associated radar ... Interferometrie SAR J.T. Mayhan Group 32 Technical Report ] 135 28 December 2()(W Approved for public release; distribution is unlimited. Lexington...inverse synthetie aperture radar (ISAR) images based on recent developments in high resolution spectral estimation theory. Because this technique requires

  13. Retrieval of short scale geophysical signals and improved coastal data from SAR satellite altimetry

    Science.gov (United States)

    Fenoglio-Marc, Luciana; Buchhaupt, Christopher; Dinardo, Salvatore; Scharroo, Remko; Benveniste, Jerome; Becker, Matthias

    2016-04-01

    The Delay Doppler/Synthetic Aperture Radar (SAR) altimeter offers a new quality of observational data in comparison to the pulse-limited low resolution mode (LRM) data collected over the past twenty years. Due to the reduced noise in the measurements an improved retrieval of the geophysical signal is expected in SAR. The goal of this study is to characterize these improvements both in open ocean and coastal zone using standard Level 2 and Level 1 data reprocessed with improved algorithms. We have carried out, from CryoSat-2 Level 1a Full Bit Rate (L1a FBR) data, a Delay-Doppler processing and waveform retracking tailored specifically for coastal zone by applying Hamming Window and Zero-Padding, using an extended vertical swath window in order to minimize tracker errors and a dedicated SAMOSA-based coastal retracker (named SAMOSA+). SAMOSA+ accepts mean square slope as free parameter and the epoch's first guess fitting value is decided according to the peak in correlation between 20 consecutive waveforms (in order to mitigate land off-ranging effect). Those products can be extracted from ESA-ESRIN GPOD service (named SARvatore). In order to quantify the improvement with respect to pulse-limited altimetry, we build 20 Hz PLRM (pseudo-LRM) data from CryoSat-1 L1a FBR and retrack them with numerical convolutional Brown-based retracker. Hence, here, PLRM is used as a proxy for real pulse-limited products (LRM), since there is no direct comparison of SAR and LRM possible otherwise. The PLRM data are built and retracked by Technical University of Darmstadt (TUDa). In the open ocean the study consists on the retrieval of short scale geophysical, as the swell signals. The selected areas are the CryoSat-2 Pacific and Atlantic Boxes in which it operated in SAR mode. In the coastal zone of the North Sea the study concentrates on the reduction of land and ships contamination by dedicated procedures including improved retracking. Effects of different options and retracking

  14. Moving Target Information Extraction Based on Single Satellite Image

    Directory of Open Access Journals (Sweden)

    ZHAO Shihu

    2015-03-01

    Full Text Available The spatial and time variant effects in high resolution satellite push broom imaging are analyzed. A spatial and time variant imaging model is established. A moving target information extraction method is proposed based on a single satellite remote sensing image. The experiment computes two airplanes' flying speed using ZY-3 multispectral image and proves the validity of spatial and time variant model and moving information extracting method.

  15. Locations and types of ruptures involved in the 2008 Wenchuan earthquake revealed by SAR image matching

    Science.gov (United States)

    Kobayashi, T.; Takada, Y.; Furuya, M.; Murakami, M.

    2009-12-01

    Introduction: A catastrophic earthquake with a moment magnitude of 7.9 struck China’s Sichuan area on 12 May 2008. The rupture was thought to proceed northeastward along the Longmen Shan fault zone (LMSFZ), but it remained uncertain where and how the faults were involved in the seismic event. Interferometric SAR (InSAR) analysis has an advantage of detecting ground deformation in a vast region with high precision. However, for the Sichuan event, the standard InSAR approach was not helpful in knowing the faults directly related to the seismic rupture, due to a wide coherent loss area in the proximity of the fault zone. Thus, in order to reveal the unknown surface displacements, we conducted a SAR image matching procedure that enables us to robustly detect large ground deformation even in an incoherent area. Although similar approaches can be taken with optical images to detect surface displacements, SAR images are advantageous because of the radar’s all-weather detection capability. In this presentation we will show a strong advantage of SAR data for inland large earthquakes. Analysis Method: We use ALOS/PALSAR data on the ascending orbital paths. We process the SAR data from a level-1.0 product using a software package Gamma. After conducting coregistration between two images acquired before and after the mainshock, we divide the single-look SAR amplitude images into patches and calculate an offset between the corresponding patches by an intensity tracking method. This method is performed by cross-correlating samples of backscatter intensity of a master image with those of a slave image. To reduce the artificial offsets in range component, we apply an elevation dependent correction incorporating SRTM3 DEM data. Results: We have successfully obtained the surface deformation in range component: A sharp displacement discontinuity with a relative motion of 1-2 m appears over a length of 200 km along the LMSFZ, which demonstrates that the main rupture has proceeded

  16. Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region

    Directory of Open Access Journals (Sweden)

    Tao Zhou

    2017-05-01

    Full Text Available Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A and optical (Landsat-8 data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM and a random forest (RF method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure–up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data.

  17. Controls on slow-moving landslides revealed by satellite and airborne InSAR

    Science.gov (United States)

    Handwerger, Alexander L.; Fielding, Eric J.

    2017-04-01

    Landslides display a wide variety of behaviors ranging from slow persistent motion to rapid acceleration and catastrophic failure. Given the variety of possible behaviors, improvements to our understanding of landslide mechanics are critical for accurate predictions of landslide dynamics. To better constrain the mechanisms that control landslide motion, we use recent SAR data collected by Copernicus Sentinel-1A/B, NASA UAVSAR, JAXA ALOS-2, and DLR TerraSAR-X to quantify the time-dependent kinematics of over 200 slow-moving landslides in the Central and Northern California Coast Ranges. These landslides are ideally suited for InSAR investigations due to their size (up to 5 km in length and 0.5 km in width), persistent downslope motion with low velocities (m/yr), and sparse vegetation. We quantify the seasonal and multi-year changes in velocity driven by changes in precipitation and find that landslide velocity varies over both timescales. Over seasonal timescales, each landslide displays a period of acceleration that occurs within weeks of the onset of seasonal rainfall suggesting that motion is governed by precipitation-induced changes in pore-water pressure. We also examine the effects of multi-year climate variations (i.e., recent historic California drought and the possible wet period that began in late 2016) on the activity of landslides. We find that the drought has led to a decrease in annual displacement over the past several years and predict that a resurgence in annual displacement will occur with an increase in annual rainfall. Lastly, we use UAVSAR data acquired at 4 different look directions to quantify 3D surface displacement of multiple landslides and invert for their subsurface geometry (i.e. basal slip surface) using recently developed 3D mass conservation techniques. The application of NASA's UAVSAR data represents a major advance from previous InSAR studies on landslides in this region and provides one of the first 3D dataset that contains

  18. Lagrangian-based Backtracking of Oil Spill Dynamics from SAR Images: Application to Montara Case

    Science.gov (United States)

    Gautama, Budhi Gunadharma; Mercier, Gregoire; Fablet, Ronan; Longepe, Nicolas

    2016-08-01

    Within the framework of INDESO project (Infrastructure Development Space Oceanography), we address the issue of oilspill and aim at developing an operational SAR- based system for monitoring this issue in Indonesian waters from space. In this work, we focus on the backtrack- ing of an oilspill detected from SAR observations. As a case-study, we consider one large oil spill event that happened in Indonesian waters in 2009, referred to as the Montara oilspill. On 21 August 2009, the Montara Wellhead Platform had an uncontrolled release of hydrocarbons from one of the platform wells. It was estimated that 400 barrels (or approximately 64 tonnes) of crude oil were being lost per day. The uncontrolled release continued until 3 November 2009 and response operations continued until 3 December 2009. In this work, we develop a Langragian analysis and associated numerical inversion tools with a view to further analyzing the oil spread due to the Montara Wellhead Platform. Our model relies on a 2D Lagrangian transport model developed by CLS (Collecte Localisation Satellite). Our model involves four main parameters : the weights of wind- related and current-related advection, the origin and the duration of the oil leakage. Given SAR oilspill detections, we propose a numerical inversion of the parameters of the Lagrangian model, so that the simulated drift match the SAR observations of the oil spill. We demonstrate the relevance of the proposed model and numerical scheme for the Montara oilspill and further discuss their operational interest for the space-based oilspill backtracking and forecasting.

  19. Land cover detection with SAR images of Delta del Llobregat

    Science.gov (United States)

    Godinho, R.; Borges, P. A. V.; Calado, H.; Broquetas, A.

    2016-08-01

    This work presents a study of a multitemporal set of C-band images collected by ERS-2, aiming to understand the differentiations of the backscatter intensity and the phase coherence of different land covers to find possible synergies that could improve land cover detection. The land cover analysis allowed to observe the perfect differentiation of urban areas from intensity images. The observation of multitemporal RGB compositions combining key dates of the different points of crops growth make possible to differentiate this land cover and also to observe fluctuations inside the class itself. This fluctuations present a pattern that correspond to the crop field structure, which suggests that more information can be obtained. The shrubs are difficult to detect from the intensity images, but once the observation is combined with coherence images the detection is possible. However, the coherence image must be generated from pairs of images with a temporal interval lower than three months, independently from the year of registration of each image due to the general decrease of coherence when larger intervals are used. The analysis allowed to observe the potential of this data to perfect distinguish urban, crops and shrubs. The study of the seasonal fluctuations of intensity for the crops land cover with precise ground truth for crops type and points of growth is proposed as a future line of research.

  20. Spotlight SAR sparse sampling and imaging method based on compressive sensing

    Institute of Scientific and Technical Information of China (English)

    XU HuaPing; YOU YaNan; LI ChunSheng; ZHANG LvQian

    2012-01-01

    Spotlight synthetic aperture radar (SAR) emits a chirp signal and the echo bandwidth can be reduced through dechirp processing,where the A/D sampling rate decreases accordingly at the receiver.Compressive sensing allows the compressible signal to be reconstructed with a high probability using only a few samples by solving a linear program problem.This paper presents a novel signal sampling and imaging method for application to spotlight SAR based on compressive sensing.The signal is randomly sampled after dechirp processing to form a low-dimensional sample set,and the dechirp basis is imported to reconstruct the dechirp signal.Matching pursuit (MP) is used as a reconstruction algorithm.The reconstructed signal uses polar format algorithm (PFA) for imaging.Although our novel mechanism increases the system complexity to an extent,the data storage requirements can be compressed considerably. Several simulations verify the feasibility and accuracy of spotlight SAR signal processing via compressive sensing,and the method still obtains acceptable imaging results with 10% of the original echo data.

  1. a SAR Intensity Images Change Detection Method Based on Fusion Difference Detector and Statistical Properties

    Science.gov (United States)

    Cui, B.; Zhang, Y.; Yan, L.; Cai, X.

    2017-09-01

    Detecting the land cover changes is an important application of multi-temporal synthetic aperture radar (SAR) images. This study puts forward a novel SAR change detection method which has two-steps: change detector construction and change threshold selection. For change detector construction, considering the SAR intensity images follow the gamma distribution, the conditional probabilities of the binary hypothesis test are provided, then the log likelihood ratio (LLR) combined with the log ratio (LR) to construct a detector which can enhance the degree of change to calculate the diversity degree convenient between the two images; for change threshold selection, owing to the characteristic that the curve about the ratio value of adjacent grey-level (GL) values in normalized difference map, the normalized difference map can be segmented in three parts by two thresholds selected which correspond to the regions of unchanged, backscatter enhanced and weakened separately. And as this, the change areas can be also determined simultaneously. The experimental results on different areas and sensors indicate that the proposed algorithm is effective and feasible.

  2. THERMAL AND VISIBLE SATELLITE IMAGE FUSION USING WAVELET IN REMOTE SENSING AND SATELLITE IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    A. H. Ahrari

    2017-09-01

    Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.

  3. Automatic oil slick detection from SAR images: Results and improvements in the framework of the PRIMI pilot project

    Science.gov (United States)

    Trivero, Paolo; Adamo, Maria; Biamino, Walter; Borasi, Maria; Cavagnero, Marco; De Carolis, Giacomo; Di Matteo, Lorenza; Fontebasso, Fabio; Nirchio, Francesco; Tataranni, Francesco

    2016-11-01

    An automatic system capable of discriminating oil spills from other similar sea surface features in Synthetic Aperture Radar images has been developed and tested. This system, called Oil Spill Automatic Detector (OSAD), was originally conceived for C-band SAR images (mostly ERS PRI) and afterward adapted to ENVISAT data. In the framework of the Progetto pilota Rilevamento Inquinamento Marino da Idrocarburi (PRIMI) national project sponsored by the Italian Space Agency, the OSAD system has been greatly improved and is now able to process L- and X-band images from various satellites as well. OSAD performance, confirmed using a different dataset of verified slicks, shows an a priori overall correct classification of 80%. Moreover, new features have been added, such as an enhanced land masking algorithm, a built-in wind and wave extraction module, and oil spill characterization. OSAD has been integrated into a complex hardware and software architecture for operational sea monitoring, alarm generation, and oil slick drift forecasting. The system's detection capabilities have been validated during a measurement campaign in the Mediterranean Sea. The new improved system is described herein, with special attention to latest enhancements.

  4. Site Scale Wetness Classification of Tundra Regions with C-Band SAR Satellite Data

    Science.gov (United States)

    Widhalm, Barbara; Bartsch, Annett; Siewert, Matthias Benjamin; Gugelius, Gustaf; Elberling, Bo; Leibman, Marina; Dvornikov, Yury; Khomutov, Artem

    2016-08-01

    A representative and consistent wetland map for the circumpolar region is required for a range of applications including modelling of permafrost properties as well as upscaling of carbon pools and fluxes. Synthetic Aperture Radar (SAR) data has been shown to be suitable for wetland mapping, especially C- band ASAR GM data (1-km resolution). A circumpolar wetness classification map has been introduced previously [1].With heterogeneity being a major challenge in the Arctic, higher spatial resolution products than GM are essential. In this study we therefore investigate the potential of this approach at site scale using ENVISAT ASAR WS data ( 120 m resolution). These higher resolution ASAR WS maps have been produced for study sites representing different settings throughout the Arctic and compared to high resolution land cover maps and field survey data.It can be shown that a medium resolution C-band SAR based wetness level map can be derived for tundra regions where no scattering due to tree trunks hampers the applied methodology.

  5. Comparing Accuracy of Airborne Laser Scanning and TerraSAR-X Radar Images in the Estimation of Plot-Level Forest Variables

    Directory of Open Access Journals (Sweden)

    Juha Hyyppä

    2010-01-01

    Full Text Available In this study we compared the accuracy of low-pulse airborne laser scanning (ALS data, multi-temporal high-resolution noninterferometric TerraSAR-X radar data and a combined feature set derived from these data in the estimation of forest variables at plot level. The TerraSAR-X data set consisted of seven dual-polarized (HH/HV or VH/VV Stripmap mode images from all seasons of the year. We were especially interested in distinguishing between the tree species. The dependent variables estimated included mean volume, basal area, mean height, mean diameter and tree species-specific mean volumes. Selection of best possible feature set was based on a genetic algorithm (GA. The nonparametric k-nearest neighbour (k-NN algorithm was applied to the estimation. The research material consisted of 124 circular plots measured at tree level and located in the vicinity of Espoo, Finland. There are large variations in the elevation and forest structure in the study area, making it demanding for image interpretation. The best feature set contained 12 features, nine of them originating from the ALS data and three from the TerraSAR-X data. The relative RMSEs for the best performing feature set were 34.7% (mean volume, 28.1% (basal area, 14.3% (mean height, 21.4% (mean diameter, 99.9% (mean volume of Scots pine, 61.6% (mean volume of Norway spruce and 91.6% (mean volume of deciduous tree species. The combined feature set outperformed an ALS-based feature set marginally; in fact, the latter was better in the case of species-specific volumes. Features from TerraSAR-X alone performed poorly. However, due to favorable temporal resolution, satellite-borne radar imaging is a promising data source for updating large-area forest inventories based on low-pulse ALS.

  6. Generalized interpretation scheme for arbitrary HR InSAR image pairs

    Science.gov (United States)

    Boldt, Markus; Thiele, Antje; Schulz, Karsten

    2013-10-01

    Land cover classification of remote sensing imagery is an important topic of research. For example, different applications require precise and fast information about the land cover of the imaged scenery (e.g., disaster management and change detection). Focusing on high resolution (HR) spaceborne remote sensing imagery, the user has the choice between passive and active sensor systems. Passive systems, such as multispectral sensors, have the disadvantage of being dependent from weather influences (fog, dust, clouds, etc.) and time of day, since they work in the visible part of the electromagnetic spectrum. Here, active systems like Synthetic Aperture Radar (SAR) provide improved capabilities. As an interactive method analyzing HR InSAR image pairs, the CovAmCohTM method was introduced in former studies. CovAmCoh represents the joint analysis of locality (coefficient of variation - Cov), backscatter (amplitude - Am) and temporal stability (coherence - Coh). It delivers information on physical backscatter characteristics of imaged scene objects or structures and provides the opportunity to detect different classes of land cover (e.g., urban, rural, infrastructure and activity areas). As example, railway tracks are easily distinguishable from other infrastructure due to their characteristic bluish coloring caused by the gravel between the sleepers. In consequence, imaged objects or structures have a characteristic appearance in CovAmCoh images which allows the development of classification rules. In this paper, a generalized interpretation scheme for arbitrary InSAR image pairs using the CovAmCoh method is proposed. This scheme bases on analyzing the information content of typical CovAmCoh imagery using the semisupervised k-means clustering. It is shown that eight classes model the main local information content of CovAmCoh images sufficiently and can be used as basis for a classification scheme.

  7. Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

    Science.gov (United States)

    Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.

    2016-06-01

    Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

  8. LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

    Directory of Open Access Journals (Sweden)

    I. Schvartzman

    2016-06-01

    Full Text Available Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010. The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA data.

  9. SAR moving target imaging using sparse and low-rank decomposition

    Science.gov (United States)

    Ni, Kang-Yu; Rao, Shankar

    2014-05-01

    We propose a method to image a complex scene with spotlight synthetic aperture radar (SAR) despite the presence of multiple moving targets. Many recent methods use sparsity-based reconstruction coupled with phase error corrections of moving targets to reconstruct stationary scenes. However, these methods rely on the assumption that the scene itself is sparse and thus unfortunately cannot handle realistic SAR scenarios with complex backgrounds consisting of more than just a few point targets. Our method makes use of sparse and low-rank (SLR) matrix decomposition, an efficient method for decomposing a low-rank matrix and sparse matrix from their sum. For detecting the moving targets and reconstructing the stationary background, SLR uses a convex optimization model that penalizes the nuclear norm of the low rank background structure and the L1 norm of the sparse moving targets. We propose an L1-norm regularization reconstruction method to form the input data matrix, which is grossly corrupted by the moving targets. Each column of the input matrix is a reconstructed SAR image with measurements from a small number of azimuth angles. The use of the L1-norm regularization and a sparse transform permits us to reconstruct the scene with significantly fewer measurements so that moving targets are approximately stationary. We demonstrate our SLR-based approach using simulations adapted from the GOTCHA Volumetric SAR data set. These simulations show that SLR can accurately image multiple moving targets with different individual motions in complex scenes where methods that assume a sparse scene would fail.

  10. Prediction of water quality parameters from SAR images by using multivariate and texture analysis models

    Science.gov (United States)

    Shareef, Muntadher A.; Toumi, Abdelmalek; Khenchaf, Ali

    2014-10-01

    Remote sensing is one of the most important tools for monitoring and assisting to estimate and predict Water Quality parameters (WQPs). The traditional methods used for monitoring pollutants are generally relied on optical images. In this paper, we present a new approach based on the Synthetic Aperture Radar (SAR) images which we used to map the region of interest and to estimate the WQPs. To achieve this estimation quality, the texture analysis is exploited to improve the regression models. These models are established and developed to estimate six common concerned water quality parameters from texture parameters extracted from Terra SAR-X data. In this purpose, the Gray Level Cooccurrence Matrix (GLCM) is used to estimate several regression models using six texture parameters such as contrast, correlation, energy, homogeneity, entropy and variance. For each predicted model, an accuracy value is computed from the probability value given by the regression analysis model of each parameter. In order to validate our approach, we have used tow dataset of water region for training and test process. To evaluate and validate the proposed model, we applied it on the training set. In the last stage, we used the fuzzy K-means clustering to generalize the water quality estimation on the whole of water region extracted from segmented Terra SAR-X image. Also, the obtained results showed that there are a good statistical correlation between the in situ water quality and Terra SAR-X data, and also demonstrated that the characteristics obtained by texture analysis are able to monitor and predicate the distribution of WQPs in large rivers with high accuracy.

  11. Application of Multifractal Analysis to Segmentation of Water Bodies in Optical and Synthetic Aperture Radar Satellite Images

    CERN Document Server

    Martin, Victor Manuel San

    2016-01-01

    A method for segmenting water bodies in optical and synthetic aperture radar (SAR) satellite images is proposed. It makes use of the textural features of the different regions in the image for segmentation. The method consists in a multiscale analysis of the images, which allows us to study the images regularity both, locally and globally. As results of the analysis, coarse multifractal spectra of studied images and a group of images that associates each position (pixel) with its corresponding value of local regularity (or singularity) spectrum are obtained. Thresholds are then applied to the multifractal spectra of the images for the classification. These thresholds are selected after studying the characteristics of the spectra under the assumption that water bodies have larger local regularity than other soil types. Classifications obtained by the multifractal method are compared quantitatively with those obtained by neural networks trained to classify the pixels of the images in covered against uncovered b...

  12. The imaging algorithm of millimeter-wave forward-looking SAR

    Science.gov (United States)

    Chen, Lei; Li, Xingguang; Chen, Dianren

    2017-01-01

    It is studied a new type millimeter-wave forward-looking synthetic aperture radar (SAR) imaging algorithm in this paper, analyzes the imaging principle, echo model of point target is given, deduced the forward-looking synthetic aperture radar RD imaging algorithm, and using MATLAB imaging simulation of point target in 6, a point target simulation results from the peak of 64 * 64 slice contour and azimuth, distance to the envelope of the imaging results were analyzed, found that the distance and azimuth focusing effect is good and the side lobe does not appear distorted and tilted, proved that the system of the millimeter wave synthetic aperture radar imaging of forward-looking , simulation results demonstrate the validity of the system.

  13. Case study on the extraction of land cover information from the SAR image of a coal mining area

    Institute of Scientific and Technical Information of China (English)

    HU Zhao-ling; LI Hai-quan; DU Pei-jun

    2009-01-01

    In this study, analyses are conducted on the information features of a construction site, a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area, on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image, we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next, a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis, a classification is conducted selectively on three principal component bands with the most information. Finally, through training and experimenting with the samples, a better three-layered BP neural network was established to classify the SAR image. The results show that, assisted by texture information, the neural network classification improved the accuracy of SAR image clas-sification by 14.6%, compared with a classification by maximum likelihood estimation without texture information.

  14. New Approach for Unambiguous High-Resolution Wide-Swath SAR Imaging

    Directory of Open Access Journals (Sweden)

    Yueguan Lin

    2014-01-01

    Full Text Available The high-resolution wide-swath (HRWS SAR system uses a small antenna for transmitting waveform and multiple antennas both in elevation and azimuth for receiving echoes. It has the potential to achieve wide spatial coverage and fine azimuth resolution, while it suffers from elevation pattern loss caused by the presence of topographic height and impaired azimuth resolution caused by nonuniform sampling. A new approach for HRWS SAR imaging based on compressed sensing (CS is introduced. The data after range compression of multiple elevation apertures are used to estimate direction of arrival (DOA of targets via CS, and the adaptive digital beamforming in elevation is achieved accordingly, which avoids the pattern loss of scan-on-receive (SCORE algorithm when topographic height exists. The effective phase centers of the system are nonuniformly distributed when displaced phase center antenna (DPCA technology is adopted, which causes Doppler ambiguities under traditional SAR imaging algorithms. Azimuth reconstruction based on CS can resolve this problem via precisely modeling the nonuniform sampling. Validation with simulations and experiment in an anechoic chamber are presented.

  15. Imaging of buried and foliage-obscured objects with an ultrawide-bandwidth polarimetric SAR

    Science.gov (United States)

    Sheen, Dan R.; Lewis, Terry B.; Wei, Susan C.; Kletzli, D. W., Jr.

    1993-11-01

    The Environmental Research Institute of Michigan (ERIM) has developed a unique ground- based, portable, synthetic aperture radar (SAR). This SAR images targets in their natural backgrounds without the expense of an airborne sensor and with higher performance (bandwidth, resolution) than existing airborne systems. A horizontal 36-foot long aluminum truss supports a rail and an antenna cartridge, which is moved along the rail to allow synthetic aperture focusing. The system is fully-polarimetric and has collected data over the frequency band of 400 - 1300 MHz resulting in a nominal resolution of 0.17 m in range and 0.5 m in cross-range. The low frequency range of the system allows for penetration of soil (to shallow depths) as well as foliage and the system has been used to collect images of buried and foliage- obscured targets. The ground imagery collected to date includes steel oil drums buried at depths of up to one-meter. Both the drums as well as the disturbances due to digging the holes are visible in the imagery. Foliage imagery includes portions of a Lear jet under a mature hardwood forest. Due to the low frequency and wide bandwidth of the sensor (400 - 1300 MHz), obscured objects are clearly visible in the SAR imagery. Other responses in the foliage imagery are due to the dihedral-like ground-trunk reflections.

  16. Land Cover Classification for Polarimetric SAR Images Based on Mixture Models

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2014-04-01

    Full Text Available In this paper, two mixture models are proposed for modeling heterogeneous regions in single-look and multi-look polarimetric SAR images, along with their corresponding maximum likelihood classifiers for land cover classification. The classical Gaussian and Wishart models are suitable for modeling scattering vectors and covariance matrices from homogeneous regions, while their performance deteriorates for regions that are heterogeneous. By comparison, the proposed mixture models reduce the modeling error by expressing the data distribution as a weighted sum of multiple component distributions. For single-look and multi-look polarimetric SAR data, complex Gaussian and complex Wishart components are adopted, respectively. Model parameters are determined by employing the expectation-maximization (EM algorithm. Two maximum likelihood classifiers are then constructed based on the proposed mixture models. These classifiers are assessed using polarimetric SAR images from the RADARSAT-2 sensor of the Canadian Space Agency (CSA, the AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the EMISAR sensor of the Technical University of Denmark (DTU. Experiment results demonstrate that the new models fit heterogeneous regions preferably to the classical models and are especially appropriate for extremely heterogeneous regions, such as urban areas. The overall accuracy of land cover classification is also improved due to the more refined modeling.

  17. A novel polar format algorithm for SAR images utilizing post azimuth transform interpolation.

    Energy Technology Data Exchange (ETDEWEB)

    Holzrichter, Michael Warren; Martin, Grant D.; Doerry, Armin Walter

    2005-09-01

    SAR phase history data represents a polar array in the Fourier space of a scene being imaged. Polar Format processing is about reformatting the collected SAR data to a Cartesian data location array for efficient processing and image formation. In a real-time system, this reformatting or ''re-gridding'' operation is the most processing intensive, consuming the majority of the processing time; it also is a source of error in the final image. Therefore, any effort to reduce processing time while not degrading image quality is valued. What is proposed in this document is a new way of implementing real-time polar-format processing through a variation on the traditional interpolation/2-D Fast Fourier Transform (FFT) algorithm. The proposed change is based upon the frequency scaling property of the Fourier Transform, which allows a post azimuth FFT interpolation. A post azimuth processing interpolation provides overall benefits to image quality and potentially more efficient implementation of the polar format image formation process.

  18. Advanced Interferometric Synthetic Aperture Imaging Radar (InSAR) for Dune Mapping

    Science.gov (United States)

    Havivi, Shiran; Amir, Doron; Schvartzman, Ilan; August, Yitzhak; Mamman, Shimrit; Rotman, Stanely R.; Blumberg, Dan G.

    2016-04-01

    Aeolian morphologies are formed in the presence of sufficient wind energy and available lose particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970s, remote sensing imagery, both optical and radar, have been used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two or more images. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR methods. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This work aims to demonstrate how interferometric decorrelation can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the coherence change detection method was used, in order to identify dune stability or instability and the dune activity level. The Nitzanim-Ashdod coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of

  19. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    KAUST Repository

    Wang, Teng

    2015-02-03

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  20. First Experiment of IECAS P-Band Quad-Pol SAR System in Circular Imaging Mode

    Science.gov (United States)

    Hong, Wen; Li, Yang; Yin, Qiang; Lin, Yun; Chen, Erxue; Pottier, Eric

    2013-01-01

    Within the framework of the DRAGON2 project, the Institute of Electronics, Chinese Academy of Sciences (IECAS) continuously had a tight collaboration with the European and the Chinese partners. Our contribution to the joint research, separated by 4 working packages: land cover analysis, earth surface deformation monitoring and DEM extraction, forest vertical structure parameters extraction, and PolSARpro software continued development, is reviewed in the beginning. Furthermore, a joint study between IECAS - NKLMIT and University of Rennes-1 -Institute of Electronics and Telecommunications, about DEM based soil moisture inversion using POLSAR data is reviewed. Besides, a compact-pol calibration algorithm for a wide-band ground-based SAR system and a supervised land cover classification method are proposed here. Finally, the first experiment of IECAS P-band quad-pol SAR system in circular imaging mode is introduced.

  1. Satellite-based monitoring of grassland: assessment of harvest dates and frequency using SAR

    Science.gov (United States)

    Siegmund, R.; Grant, K.; Wagner, M.; Hartmann, S.

    2016-10-01

    Grasslands are among the largest ecosystems worldwide and according to the FAO they contribute to the livelihoods of more than 800 million people. Harvest dates and frequency can be utilised for an improved estimation of grassland yields. In the presented project a highly automatised methodology for detecting harvest dates and frequency using SARamplitude data was developed based on an amplitude change detection techniques. This was achieved by evaluating spatial statistics over field boundaries provided by the European Integrated Administration and Control System (IACS) to identify changes between pre- and post-harvest acquisitions. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. In our contribution we will focus on SAR-remote sensing for monitoring harvest frequencies, discuss the requirements concerning the acquisition system, present the technical approach and analyse the verified results. In terms of the acquisition system a high temporal acquisition rate is required, which is generally met by using SARsatellite constellations providing a revisit time of few days. COSMO-SkyMed data were utilised for the pilot study for developing and prototyping a monitoring system. Subsequently the approach was adapted to the use of the C-Band system Sentinel-1A becoming fully operational with the availability of Sentinal-1B. The study area is situated northeast of Munich, Germany, extending to an area of approx. 40km to 40km and covering major verification sites and in-situ data provided by research farms or continuously surveyed in-situ campaigns. An extended time series of SAR data was collected during the cultivation and vegetation cycles between March 2014 and March 2016. All data were processed and harmonised in a GIS database to be analysed and verified according to corresponding in-situ data.

  2. PS-InSAR Monitoring of Landslide Activity in the Black Sea Coast of the Caucasus

    NARCIS (Netherlands)

    Kiseleva, E.; Mikhailov, V.; Smolyaninova, E.; Dmitriev, P.; Golubev, V.; Timoshkina, E.; Hooper, A.; Samiei-Esfahany, S.; Hanssen, R.F.

    2014-01-01

    The landslide activity in the area of Bolshoy Sochi (Big Sochi) situated at the Black Sea coast of the Great Caucasus has been studied using the StaMPS PS-InSAR method. We incorporated three sets of radar images from the satellites with different wavelengths ALOS, Envisat and Terra-SAR-X from both

  3. PS-InSAR Monitoring of Landslide Activity in the Black Sea Coast of the Caucasus

    NARCIS (Netherlands)

    Kiseleva, E.; Mikhailov, V.; Smolyaninova, E.; Dmitriev, P.; Golubev, V.; Timoshkina, E.; Hooper, A.; Samiei-Esfahany, S.; Hanssen, R.F.

    2014-01-01

    The landslide activity in the area of Bolshoy Sochi (Big Sochi) situated at the Black Sea coast of the Great Caucasus has been studied using the StaMPS PS-InSAR method. We incorporated three sets of radar images from the satellites with different wavelengths ALOS, Envisat and Terra-SAR-X from both a

  4. Detection and Imaging of Slowly Moving Target of Airborne SAR Based on the GMCWD-Hough Transform

    Institute of Scientific and Technical Information of China (English)

    WANGLing; TAORar; ZHOUSiyong; WANGYue

    2004-01-01

    In this paper, the features of airborne SAR moving target echoes are analysed, the Generalizedmarginal Choi-Williams Distribution-Hough transform (GMCWD-HT) is also introduced. According to the echo model of airborne SAR, a new method based on the Generalized-marginal Choi-Williams Distribution-Hough transform for detecting and imaging the slowly moving targets of airborne SAR is proposed in the paper. This method can be used to perform the slowly moving target detection and imaging of airborne SAR in the low signal to clutter ratio, its detecting performance is better than the common method based on Wigner-Ville distribution. Computer simulation results have proven the validity of the approach.

  5. NanoSAR – Case study of synthetic aperture radar for nano-satellites

    NARCIS (Netherlands)

    Engelen, S.; Oever, M. van den; Mahapatra, P.S.; Sundaramoorthy, P.P.; Gill, E.K.A.; Meijer, R.J.; Verhoeven, C.J.M.

    2012-01-01

    Nano-satellites have a cost advantage due to their low mass and usage of commercial-off-the-shelf technologies. However, the low mass also restricts the functionality of a nano-satellite’s payload. Typically, this would imply instruments with very low to low resolution and accuracy, essentially

  6. Great Lakes Ice Cover Classification and Mapping Using Satellite Synthetic Aperture Radar (SAR) Data

    Science.gov (United States)

    Nghiem, S.; Leshkevich, G.; Kwok, R.

    1998-01-01

    Owing to the size and extent of the Great Lakes and the variety of ice types features found there, the timely and objective qualities inherent in computer processing of satellite data make it well suited for monitoring and mapping ice cover.

  7. Impact of the timing of a SAR image acquisition on the calibration of a flood inundation model

    Science.gov (United States)

    Gobeyn, Sacha; Van Wesemael, Alexandra; Neal, Jeffrey; Lievens, Hans; Eerdenbrugh, Katrien Van; De Vleeschouwer, Niels; Vernieuwe, Hilde; Schumann, Guy J.-P.; Di Baldassarre, Giuliano; Baets, Bernard De; Bates, Paul D.; Verhoest, Niko E. C.

    2017-02-01

    Synthetic Aperture Radar (SAR) data have proven to be a very useful source of information for the calibration of flood inundation models. Previous studies have focused on assigning uncertainties to SAR images in order to improve flood forecast systems (e.g. Giustarini et al. (2015) and Stephens et al. (2012)). This paper investigates whether the timing of a SAR acquisition of a flood has an important impact on the calibration of a flood inundation model. As no suitable time series of SAR data exists, we generate a sequence of consistent SAR images through the use of a synthetic framework. This framework uses two available ERS-2 SAR images of the study area, one taken during the flood event of interest, the second taken during a dry reference period. The obtained synthetic observations at different points in time during the flood event are used to calibrate the flood inundation model. The results of this study indicate that the uncertainty of the roughness parameters is lower when the model is calibrated with an image taken before rather than during or after the flood peak. The results also show that the error on the modelled extent is much lower when the model is calibrated with a pre-flood peak image than when calibrated with a near-flood peak or a post-flood peak image. It is concluded that the timing of the SAR image acquisition of the flood has a clear impact on the model calibration and consequently on the precision of the predicted flood extent.

  8. Group sparsity based airborne wide angle SAR imaging

    Science.gov (United States)

    Wei, Zhonghao; Zhang, Bingchen; Bi, Hui; Lin, Yun; Wu, Yirong

    2016-10-01

    In this paper, we develop a group sparsity based wide angle synthetic aperture radar (WASAR) imaging model and propose a novel algorithm called backprojection based group complex approximate message passing (GCAMP-BP) to recover the anisotropic scene. Compare to conventional backprojection based complex approximate message passing (CAMP-BP) algorithm for the recovery of isotropic scene, the proposed method accommodates aspect dependent scattering behavior better and can produce better imagery. Simulated and experimental results are presented to demonstrate the validity of the proposed algorithm.

  9. Satellite image eavesdropping: a multidisciplinary science education project

    Energy Technology Data Exchange (ETDEWEB)

    Friedt, Jean-Michel [Association Projet Aurore, UFR-ST La Bouloie, 16, route de Gray, 25030 Besancon Cedex (France)

    2005-11-01

    Amateur reception of satellite images gathers a wide number of concepts and technologies which makes it attractive as an educational tool. We here introduce the reception of images emitted from NOAA series low-altitude Earth-orbiting satellites. We tackle various issues including the identification and prediction of the pass time of visible satellites, the building of the radio-frequency receiver and antenna after modelling their radiation pattern, and then the demodulation of the resulting audio signal for finally displaying an image of the Earth as seen from space.

  10. The Load Design and Implementation of HJ-1-C Space-borne SAR

    OpenAIRE

    Yu Wei-dong; Yang Ru-liang; Deng Yun-kai; Zhao Feng-jun; Lei Hong

    2014-01-01

    HJ-1-C is a Synthetic Aperture Radar (SAR) satellite in the Constellation of “2+1” for China environment and disaster monitoring. It works at S-band with a resolution of 5 m. SAR payload uses a reflector antenna and a high-power concentrated transmitter. Its light weight and high efficiency is very suitable for a small satellite platform. Now HJ-1-C satellite has been launched into orbit and has acquired Chinese first S-band SAR images from space, which demonstrate excellent quality and rich ...

  11. QBP Imaging Algorithm for the Bistatic SAR%双基地SAR的QBP成像算法

    Institute of Scientific and Technical Information of China (English)

    徐三元; 王建国

    2011-01-01

    The standard backprojection ( BP) algorithm can flexibly deal with bistatic SAR signal data , but its computational load is heavy. It is shown that the azimuth bandwidth of the bistatic SAR is proportional to the size of the imaging patch after SAR signal is spotlighted , and the quadtree backprojeetion ( BP) algorithm can provide a large reduccion of the computational load compared to the standard backprojection algorithm. The effect on change in spotlight reference points signal bandwidth is discussed and an implementation of the quadtree backprojection algorithm is presented. Computational complexity of the algorithm is analyzed. The theoretical analysis, simulation results and the experimental data processing confirm that the algorithm is effective.%时域BP算法能够灵活处理双基地SAR信号,但是运算量很大.本文根据系统工作模型,推导出SAR信号聚束化后方位向带宽与成像区域的尺寸成正比,适合采用QBP算法进行成像;研究了聚束参考点的变化对信号带宽的影响.给出了双基地QBP算法的具体实现步骤,分析了QBP算法的运算复杂度.理论分析、仿真实验和实测数据结果验证了QBP算法的有效性.

  12. Dual-Branch Deep Convolution Neural Network for Polarimetric SAR Image Classification

    Directory of Open Access Journals (Sweden)

    Fei Gao

    2017-04-01

    Full Text Available The deep convolution neural network (CNN, which has prominent advantages in feature learning, can learn and extract features from data automatically. Existing polarimetric synthetic aperture radar (PolSAR image classification methods based on the CNN only consider the polarization information of the image, instead of incorporating the image’s spatial information. In this paper, a novel method based on a dual-branch deep convolution neural network (Dual-CNN is proposed to realize the classification of PolSAR images. The proposed method is built on two deep CNNs: one is used to extract the polarization features from the 6-channel real matrix (6Ch which is derived from the complex coherency matrix. The other is utilized to extract the spatial features of a Pauli RGB (Red Green Blue image. These extracted features are first combined into a fully connected layer sharing the polarization and spatial property. Then, the Softmax classifier is employed to classify these features. The experiments are conducted on the Airborne Synthetic Aperture Radar (AIRSAR data of Flevoland and the results show that the classification accuracy on 14 types of land cover is up to 98.56%. Such results are promising in comparison with other state-of-the-art methods.

  13. An improved PolSAR image speckle reduction algorithm based on LMMSE and RICA

    Science.gov (United States)

    Jiang, Chang; He, Xiufeng

    2017-07-01

    Although the linear minimum mean square error (LMMSE) filter removes speckle in polarimetric synthetic aperture radar (PolSAR) images, it has the disadvantage of losing edge detail. In this paper, we propose a new filter based on robust independent component analysis (RICA) and LMMSE. This approach describes edge features in a span image by selecting the adaptive direction window and calculating the edge weight value of the spatial domain, and improves the objective function by using a step polynomial to extract the estimate of the source image with minimum noise. This technique preserves not only the edge information in the images, but also the polarimetric information. Experiments were conducted on the NASA/JPL AIRSAR L-band of the San Francisco area, and evaluated by means of the speckle reduction index and the edge preservation index. The experimental results show that the proposed method effectively reduces speckle, retains edges, and preserves the polarimetric scattering mechanisms.

  14. RPC Modeling For Spaceborne SAR And Its Application In Radar Image Geocoding

    Science.gov (United States)

    Wei, Xiaohong; He, Xueyan; Zhang, Lu; Balz, Timo; Liao, Mingsheng

    2010-10-01

    The Rational Polynomial Coefficient (RPC) model is a typical replacement sensor model which relates image coordinates and object coordinates through rational polynomial functions. This paper investigates the methodology of RPC modeling for spaceborne SAR and its application in radar image geocoding. A hybrid approach is proposed to combine the L-curve and the IMCCV (Iteration method by correcting characteristic value) methods for RPC modeling. Experimental results show that the hybrid approach is superior to traditional methods in terms of both fitting accuracy and computation time cost. The results of different settings in RPC modeling will be shown. To ensure high accuracy of image geocoding, an additional mathematical transformation is used to remove the systematic errors in the RPC model. An Envisat ASAR image is used as experimental data to verify the application.

  15. A High-precision Motion Compensation Method for SAR Based on Image Intensity Optimization

    Directory of Open Access Journals (Sweden)

    Hu Ke-bin

    2015-02-01

    Full Text Available Owing to the platform instability and precision limitations of motion sensors, motion errors negatively affect the quality of synthetic aperture radar (SAR images. The autofocus Back Projection (BP algorithm based on the optimization of image sharpness compensates for motion errors through phase error estimation. This method can attain relatively good performance, while assuming the same phase error for all pixels, i.e., it ignores the spatial variance of motion errors. To overcome this drawback, a high-precision motion error compensation method is presented in this study. In the proposed method, the Antenna Phase Centers (APC are estimated via optimization using the criterion of maximum image intensity. Then, the estimated APCs are applied for BP imaging. Because the APC estimation equals the range history estimation for each pixel, high-precision phase compensation for every pixel can be achieved. Point-target simulations and processing of experimental data validate the effectiveness of the proposed method.

  16. SARS Basics

    Science.gov (United States)

    ... and Resources Related Links Clinician Registry Travelers' Health SARS Basics Fact Sheet Language: English Español (Spanish) Format: ... 3 pages] SARS [3 pages] SARS [3 pages] SARS? Severe acute respiratory syndrome (SARS) is a viral ...

  17. Detecting Subsidence Along a High Speed Railway by Ultrashort Baseline TCP-InSAR with High Resolution Images

    Science.gov (United States)

    Dai, K. R.; Liu, G. X.; Yu, B.; Jia, H. G.; Ma, D. Y.; Wang, X. W.

    2013-10-01

    A High Speed Railway goes across Wuqing district of Tianjin, China. Historical studies showed that the land subsidence of this area was very serious, which would give rise to huge security risk to the high speed railway. For detecting the detailed subsidence related to the high speed railway, we use the multi-temporal InSAR (MT-InSAR) technique to extract regional scale subsidence of Wuqing district. Take it into consideration that Wuqing district is a suburban region with large area of low coherence farmland, we select the temporarily coherent point InSAR (TCP-InSAR) approach for MT-InSAR analysis. The TCP-InSAR is a potential approach for detecting land subsidence in low coherence areas as it can identify and analysis coherent points between just two images and can acquire a reliable solution without conventional phase unwrapping. This paper extended the TCP-InSAR with use of ultrashort spatial baseline (USB) interferograms. As thetopographic effects are negligible in the USB interferograms, an external digital elevation model (DEM) is no longer needed in interferometric processing, and the parameters needed to be estimated were simplified at the same time. With use of 17 TerraSAR-X (TSX) images acquired from 2009 to 2010 over Wuqing district, the annual subsidence rates along the high speed railway were derived by the USB-TCPInSAR approach. Two subsidence funnels were found at ShuangJie town and around Wuqing Station with subsidence rate of -17 ∼ -27 mm/year and -7 ∼ -17 mm/year, respectively. The subsidence rates derived by USB-TCPInSAR were compared with those derived by the conventional TCP-InSAR that uses an external DEM for differential interferometry. The mean and the standard deviation of the differences between two types of results at 370697 TCPs are -4.43 × 10-6 mm/year and ±1.4673 mm/year, respectively. Further comparison with the subsidence results mentioned in several other studies were made, which shows good consistencies. The results verify

  18. Velocity estimation of an airplane through a single satellite image

    Institute of Scientific and Technical Information of China (English)

    Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

    2012-01-01

    The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

  19. Real-time optical processor prototype for remote SAR applications

    Science.gov (United States)

    Marchese, Linda; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Bourqui, Pascal; Legros, Mathieu; Desnoyers, Nichola; Guillot, Ludovic; Mercier, Luc; Savard, Maxime; Martel, Anne; Châteauneuf, François; Bergeron, Alain

    2009-09-01

    A Compact Real-Time Optical SAR Processor has been successfully developed and tested. SAR, or Synthetic Aperture Radar, is a powerful tool providing enhanced day and night imaging capabilities. SAR systems typically generate large amounts of information generally in the form of complex data that are difficult to compress. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Indeed, the first SAR images have been optically processed. The optical processor architecture provides inherent parallel computing capabilities that can be used advantageously for the SAR data processing. Onboard SAR image generation would provide local access to processed information paving the way for real-time decision-making. This could eventually benefit navigation strategy and instrument orientation decisions. Moreover, for interplanetary missions, onboard analysis of images could provide important feature identification clues and could help select the appropriate images to be transmitted to Earth, consequently helping bandwidth management. This could ultimately reduce the data throughput requirements and related transmission bandwidth. This paper reviews the design of a compact optical SAR processor prototype that would reduce power, weight, and size requirements and reviews the analysis of SAR image generation using the table-top optical processor. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and size are reviewed. Results of image generation from simulated point targets as well as real satellite-acquired raw data are presented.

  20. Using RADARSAT-2 and TerraSAR-X satellite data for the identification of canola crop phenology

    Science.gov (United States)

    Pacheco, Anna; McNairn, Heather; Li, Yifeng; Lampropoulos, George; Powers, Jarrett

    2016-10-01

    Knowing the exact growth stage of agricultural crops can be valuable information for crop management and monitoring. In Canada, canola fields are particularly vulnerable for crop disease development during their flowering stage, especially when the fields are under persistent wet conditions. Clubroot and sclerotinia are diseases that can occur in canola when these two factors come together. Remote sensing can provide an interesting tool for the monitoring of crop phenological stages over large agriculture landscapes. Reliable and frequent access to data is needed to determine field-specific growth stages. Given their all-weather capability, radar sensors are optimal for monitoring such a dynamic crop parameter. In 2014, Agriculture and Agri-Food Canada collected crop phenology information over multiple canola fields in the area of Carman, Manitoba. Coincidental to ground data collection, fully polarimetric RADARSAT-2 and dual-polarimetric TerraSAR-X satellite data were acquired over the study site. In collaboration with A. U. G. Signals Ltd., a methodology will be developed and validated for the identification of inflorescence emergence and flowering in canola fields. Analysis of the polarimetric datasets from this study determined that several polarimetric parameters were sensitive to the emergence of flower buds and the flowering stage in canola. The alpha angle and entropy in both the C- and X-band were able to identify these growth stages, in addition to any of the reflectivity ratios and differential reflectivity responses that incorporated an HV response. The RADARSAT-2 scatter diversity, degree of purity and depolarization index also demonstrated great potential at identifying canola flower emergence and flowering. These latter polarimetric parameters along with the reflectivity ratios may be advantageous given their ease in implementation within a larger risk assessment satellite-derived methodology for canola crop disease.

  1. Satellite image collection modeling for large area hazard emergency response

    Science.gov (United States)

    Liu, Shufan; Hodgson, Michael E.

    2016-08-01

    Timely collection of critical hazard information is the key to intelligent and effective hazard emergency response decisions. Satellite remote sensing imagery provides an effective way to collect critical information. Natural hazards, however, often have large impact areas - larger than a single satellite scene. Additionally, the hazard impact area may be discontinuous, particularly in flooding or tornado hazard events. In this paper, a spatial optimization model is proposed to solve the large area satellite image acquisition planning problem in the context of hazard emergency response. In the model, a large hazard impact area is represented as multiple polygons and image collection priorities for different portion of impact area are addressed. The optimization problem is solved with an exact algorithm. Application results demonstrate that the proposed method can address the satellite image acquisition planning problem. A spatial decision support system supporting the optimization model was developed. Several examples of image acquisition problems are used to demonstrate the complexity of the problem and derive optimized solutions.

  2. Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

  3. Kansas Satellite Image Database (KSID) 2004-2005

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...

  4. Ship Targets Discrimination Algorithm in SAR Images Based on Hu Moment Feature and Texture Feature

    Directory of Open Access Journals (Sweden)

    Liu Lei

    2016-01-01

    Full Text Available To discriminate the ship targets in SAR images, this paper proposed the method based on combination of Hu moment feature and texture feature. Firstly,7 Hu moment features should be extracted, while gray level co-occurrence matrix is then used to extract the features of mean, variance, uniformity, energy, entropy, inertia moment, correlation and differences. Finally the k-neighbour classifier was used to analysis the 15 dimensional feature vectors. The experimental results show that the method of this paper has a good effect.

  5. Spatial Cloud Detection and Retrieval System for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ayman Nasr

    2013-01-01

    Full Text Available In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection. Satellite images having a large percentage of cloud cannot be used in further analysis. While there are many approaches that deal with different semantic meaning, there are rarely approaches that deal specifically with cloud detection and retrieval. In this paper we introduce a novel approach that spatially detect and retrieve clouds in satellite images using their unique properties .Our approach is developed as spatial cloud detection and retrieval system (SCDRS that introduce a complete framework for specific semantic retrieval system. It uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tile sizes using spatial and textural properties of cloud regions. Second, we retrieve our tiles using a parametric statistical approach within a multilevel refinement process. Our approach has been experimentally validated against the conventional ones yielding enhanced precision and recall rates in the same time it gives more precise detection of cloud coverage regions.

  6. GOTCHA experience report: three-dimensional SAR imaging with complete circular apertures

    Science.gov (United States)

    Ertin, Emre; Austin, Christian D.; Sharma, Samir; Moses, Randolph L.; Potter, Lee C.

    2007-04-01

    We study circular synthetic aperture radar (CSAR) systems collecting radar backscatter measurements over a complete circular aperture of 360 degrees. This study is motivated by the GOTCHA CSAR data collection experiment conducted by the Air Force Research Laboratory (AFRL). Circular SAR provides wide-angle information about the anisotropic reflectivity of the scattering centers in the scene, and also provides three dimensional information about the location of the scattering centers due to a non planar collection geometry. Three dimensional imaging results with single pass circular SAR data reveals that the 3D resolution of the system is poor due to the limited persistence of the reflectors in the scene. We present results on polarimetric processing of CSAR data and illustrate reasoning of three dimensional shape from multi-view layover using prior information about target scattering mechanisms. Next, we discuss processing of multipass (CSAR) data and present volumetric imaging results with IFSAR and three dimensional backprojection techniques on the GOTCHA data set. We observe that the volumetric imaging with GOTCHA data is degraded by aliasing and high sidelobes due to nonlinear flightpaths and sparse and unequal sampling in elevation. We conclude with a model based technique that resolves target features and enhances the volumetric imagery by extrapolating the phase history data using the estimated model.

  7. Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems

    Directory of Open Access Journals (Sweden)

    Stewart Santos

    2011-04-01

    Full Text Available We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA-based image enhancement approach and the “model-based” descriptive experiment design (DEED regularization paradigm are unified into a new dynamic experiment design (DYED regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

  8. CROSS-TRACK THREE APERTURES MILLIMETER WAVE SAR SIDE-LOOKING THREE-DIMENSIONAL IMAGING

    Institute of Scientific and Technical Information of China (English)

    Teng Xiumin; Li Daojing; Li Liechen; Liu Bo; Pan Zhouhao

    2012-01-01

    The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper.Three apertures are distributed along the cross-track direction,and three virtual phase centers will be obtained through one-input and three-output.These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution.Because the cross-track array is short,the cross-track resolution is low.When the system works in side-looking mode,the cross-track resolution and height resolution will be coupling,and the low cross-track resolution will partly be transformed into the height uncertainty.The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array.In order to suppress the high cross-track sidelobes,a weighting preprocessing method is proposed.The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method.And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.

  9. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

    Science.gov (United States)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

    2016-04-01

    Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

  10. GPS and Satellite InSAR Observations of Landslide Activity at the Sinking Canyon in South Central Idaho

    Science.gov (United States)

    Aly, M. H.; Glenn, N. F.; Thackray, G. D.

    2014-12-01

    Multiple rotational, transitional, and lateral spread landslides have occurred in south central Idaho where basalt lava flows overly unconsolidated lake and fluvial sediments at the Sinking Canyon. The canyon is about 0.1 km deep and 0.25-1 km wide along a 4-km segment of the Salmon Falls Creek (SFC). Local topography and hydrological conditions are most likely the major triggering factors that have initiated landslides by increasing the gravitational stresses and weakening the canyon wall materials. Landslide activity has created natural dams of SFC, which in turn has resulted in forming large lakes with a potential flooding hazard to life and property downstream. In this study, we use campaign Global Positioning System (GPS) measurements of 2003-2004 and Synthetic Aperture Radar Interferometric (InSAR) data acquired during 1992-2007 by the European radar satellites (ERS-1 and ERS-2) to identify, monitor, and analyze recent landslide activity at SFC. Results show that three main landslides have been active during the period of observation: the Salmon Falls landslide (SFL) that has been first reported in 1999, the historical 1937 landslide, and a third unnamed landslide to the north of the 1937 slide. InSAR measurements indicate that the SFL has been active during the period of our earliest interferogram (1992-1993) whereas the slide head has detached and has moved away from the eastern canyon wall about 3 cm. Over the years, the SFL body and toe have been pushed westward repetitively at rates of about 3-7 cm/yr. The toe is confined by the western canyon wall and thus is pushed upward in some years causing slight uplift (2-3 cm). Our field observations reveal many transverse and radial cracks associated with the deformation pattern caused by recurring motions. The historic 1937 slide is the largest mass wasting and is the least active landslide in the study area. The unnamed slide shows episodic activity with varying rates (0-4 cm/yr) of line-of-sight motions. This

  11. Analysis of Spectral Characteristics Based on Optical Remote Sensing and SAR Image Fusion

    Institute of Scientific and Technical Information of China (English)

    Weiguo LI; Nan JIANG; Guangxiu GE

    2014-01-01

    Because of cloudy and rainy weather in south China, optical remote sens-ing images often can't be obtained easily. With the regional trial results in Baoying, Jiangsu province, this paper explored the fusion model and effect of ENVISAT/SAR and HJ-1A satel ite multispectral remote sensing images. Based on the ARSIS strat-egy, using the wavelet transform and the Interaction between the Band Structure Model (IBSM), the research progressed the ENVISAT satel ite SAR and the HJ-1A satel ite CCD images wavelet decomposition, and low/high frequency coefficient re-construction, and obtained the fusion images through the inverse wavelet transform. In the light of low and high-frequency images have different characteristics in differ-ent areas, different fusion rules which can enhance the integration process of self-adaptive were taken, with comparisons with the PCA transformation, IHS transfor-mation and other traditional methods by subjective and the corresponding quantita-tive evaluation. Furthermore, the research extracted the bands and NDVI values around the fusion with GPS samples, analyzed and explained the fusion effect. The results showed that the spectral distortion of wavelet fusion, IHS transform, PCA transform images was 0.101 6, 0.326 1 and 1.277 2, respectively and entropy was 14.701 5, 11.899 3 and 13.229 3, respectively, the wavelet fusion is the highest. The method of wavelet maintained good spectral capability, and visual effects while improved the spatial resolution, the information interpretation effect was much better than other two methods.

  12. SAR-based Wind Resource Statistics in the Baltic Sea

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Pena Diaz, Alfredo;

    2011-01-01

    Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR) images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps...... deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images...

  13. Wave Period and Coastal Bathymetry Estimations from Satellite Images

    Science.gov (United States)

    Danilo, Celine; Melgani, Farid

    2016-08-01

    We present an approach for wave period and coastal water depth estimation. The approach based on wave observations, is entirely independent of ancillary data and can theoretically be applied to SAR or optical images. In order to demonstrate its feasibility we apply our method to more than 50 Sentinel-1A images of the Hawaiian Islands, well-known for its long waves. Six wave buoys are available to compare our results with in-situ measurements. The results on Sentinel-1A images show that half of the images were unsuitable for applying the method (no swell or wavelength too small to be captured by the SAR). On the other half, 78% of the estimated wave periods are in accordance with buoy measurements. In addition, we present preliminary results of the estimation of the coastal water depth on a Landsat-8 image (with characteristics close to Sentinel-2A). With a squared correlation coefficient of 0.7 for ground truth measurement, this approach reveals promising results for monitoring coastal bathymetry.

  14. Two-Step Single Slope/SAR ADC with Error Correction for CMOS Image Sensor

    Directory of Open Access Journals (Sweden)

    Fang Tang

    2014-01-01

    Full Text Available Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μm CMOS technology. The chip area of the proposed ADC is 7 μm × 500 μm. The measurement results show that the energy efficiency figure-of-merit (FOM of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k μm2·cycles/sample.

  15. Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation

    Directory of Open Access Journals (Sweden)

    Maria Daniela Graziano

    2016-06-01

    Full Text Available A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances.

  16. Two-step single slope/SAR ADC with error correction for CMOS image sensor.

    Science.gov (United States)

    Tang, Fang; Bermak, Amine; Amira, Abbes; Amor Benammar, Mohieddine; He, Debiao; Zhao, Xiaojin

    2014-01-01

    Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR) ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μ m CMOS technology. The chip area of the proposed ADC is 7 μ m × 500 μ m. The measurement results show that the energy efficiency figure-of-merit (FOM) of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k  μ m(2) · cycles/sample.

  17. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete

    2009-01-01

    Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy......’s Master Environmental Library. At CLS the a priori wind direction is taken from the ECMWF (European Centre of Medium-range Weather Forecasting). It is also possible to use other sources of wind direction e.g. the satellite-based ASCAT wind directions as demonstrated by CLS. The wind direction has to known...

  18. A Downward-looking Three-dimensional Imaging Method for Airborne FMCW SAR Based on Array Antennas

    Institute of Scientific and Technical Information of China (English)

    HOU Haiping; QU Changwen; ZHOU Qiang; XIANG Yingchun

    2011-01-01

    With regard to problems in conventional synthetic aperture radar (SAR), such as imaging distortion, beam limitation and failure in acquiring three-dimensional (3-D) information, a downward-looking 3-D imaging method based on frequency modulated continuous wave (FMCW) and digital beamforming (DBF) technology for airbome SAR is presented in this study. Downward-looking 3-D SAR signal model is established first, followed by introduction of virtual antenna optimization factor and discussion of equivalent-phase-center compensation. Then, compensation method is provided according to reside video phase (RVP) and slope term for FMCW SAR. As multiple receiving antennas are applied to downward-looking 3-D imaging SAR,range cell migration correction (RCMC) tums to be more complex, and corrective measures are proposed. In addition, DBF technology is applied in realizing cross-track resolution. Finally, to validate the proposed method, magnitude of slice, peak sidelobe ratio (PSLR), integrated sidelobe ratio (ISLR) and two-dimensional (2-D) contour plot of impulse response function (IRF) of point target in three dimensions are demonstrated. Satisfactory performances are shown by simulation results.

  19. A Sparse Manifold Classification Method Based on a Multi-Dimensional Descriptive Primitive of Polarimetric SAR Image Time Series

    Directory of Open Access Journals (Sweden)

    Chu He

    2017-03-01

    Full Text Available Classification using the rich information provided by time-series and polarimetric Synthetic Aperture Radar (SAR images has attracted much attention. The key point is to effectively reveal the correlation between different dimensions of information and form a joint feature. In this paper, a multi-dimensional SAR descriptive primitive for each single pixel is firstly constructed, which in the polarimetric scale obtains incoherent information through target decompositions while in the time scale obtains coherent information through stochastic walk. Secondly, for the purpose of feature extraction and dimension reduction, a special feature space mapping for the descriptive primitive of the whole image is proposed based on sparse manifold expression and compressed sensing. Finally, the above feature is inputted into a support vector machine (SVM classifier. This proposed method can inherently integrate the features of polarimetric SAR times series. Experiment results on three real time-series polarimetric SAR data sets show the effectiveness of our presented approach. The idea of a multi-dimensional descriptive primitive as a convenient tool also opens a new spectrum of potential for further processing of polarimetric SAR image time series.

  20. A Combined Use of Decomposition and Texture for Terrain Classification of Fully Polarimetric SAR Images

    Science.gov (United States)

    Rodionova, N. V.

    2007-03-01

    This p aper presents two-stag e unsupervised terrain classification of fully polarimetr ic SA R data using Freeman and Durden decomposition based on three simp le scattering mechanisms: surface, volume and double bounce (first step), and textur al features (uncorrelated uniformity , contr ast, inv erse mo men t and entropy) obtained from grey lev el co-occurrence matr ices (GLCM) (second step). Textural f eatures ar e defined in moving w indow 5x5 pixels w ith N=32 (N - number of grey lev els) . This algorith m preserves th e purity of domin ant polarimetric scattering properties and defines textural features in each scatter ing category. It is shown better object discrimin ation after app lying textur e w ith in fix ed scattering category. Speckle r eduction is one of th e main mo ments in imag e interpr etation improvement because of its great influen ce on textur e. Results from unfiltered and Lee filtered polar imetr ic SAR imag es show that the v alues of contrast and en tropy decr ease and th e values of uniformity and inverse moment increase with speckle reduction, that's tru e for all polarizations (HH, VV, HV). Th e d iscr imination b etw een objects increases after speckle f ilter ing. Polar ization influen ce on textur e features is def ined by calculating th e features in SAR images w ith HH , VV and HV polarizations before and after speck le filter ing, and then creating RG B images. It is shown mor e polarization inf luence on textur e features (uniformity , inverse mo ment and entropy) before filtering and less influen ce - after speck le f iltering. I t's not true for contrast wher e polar ization influen ce is not ch anged practically w ith filtering. SIR-C/X-SA R SLC L-band imag es of Moscow r egion are used for illustr ation.

  1. Very high resolution satellite data: New challenges in image analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...

  2. Bridge recognition of median-resolution SAR images using pun histogram entropy

    Institute of Scientific and Technical Information of China (English)

    Wenyu Wu; Dong Yin; Rong Zhang; Yan Liu; Jia Pan

    2009-01-01

    A novel algorithm for bridge recognition of median synthetic aperture radar (SAR) images using histogram entropy presented by Pun is proposed. Firstly, Lee filter and histogram proportion are used to denoise the original image and to make the target evident. Then, water regions are gained through histogram segmentation and the contours of water regions are extracted. After these, the potential bridge targets are obtained based on the space relativity between bridges and water regions using improved contour search. At last, bridges are recognized by extracting the feature of Pun histogram entropy (PHE) of these potential bridge targets. Experimental results show the good qualities of the algorithm, such as fast speed, high rate of recognition, and low rate of false target.

  3. Data Based Parameter Estimation Method for Circular-scanning SAR Imaging

    Directory of Open Access Journals (Sweden)

    Chen Gong-bo

    2013-06-01

    Full Text Available The circular-scanning Synthetic Aperture Radar (SAR is a novel working mode and its image quality is closely related to the accuracy of the imaging parameters, especially considering the inaccuracy of the real speed of the motion. According to the characteristics of the circular-scanning mode, a new data based method for estimating the velocities of the radar platform and the scanning-angle of the radar antenna is proposed in this paper. By referring to the basic conception of the Doppler navigation technique, the mathematic model and formulations for the parameter estimation are firstly improved. The optimal parameter approximation based on the least square criterion is then realized in solving those equations derived from the data processing. The simulation results verified the validity of the proposed scheme.

  4. Bayesian-based Wavelet Shrinkage for SAR Image Despeckling Using Cycle Spinning

    Institute of Scientific and Technical Information of China (English)

    ZHANG De-xiang; GAO Qing-wei; CHEN Jun-ning

    2006-01-01

    A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown. Then, a Bayesian wavelet shrinkage factor is applied to the decomposed data to estimate noise-free wavelet coefficients. The method is based on the Mixture Gaussian Distributed (MGD) modeling of sub-band coefficients. Finally, multi-resolution wavelet coefficients are reconstructed by wavelet-threshold using cycle spinning. Experimental results show that the proposed despeckling algorithm is possible to achieve an excellent balance between suppresses speckle effectively and preserves as many image details and sharpness as possible. The new method indicated its higher performance than the other speckle noise reduction techniques and minimizing the effect of pseudo-Gibbs phenomena.

  5. Change detection in polarimetric SAR images using complex Wishart distributed matrices

    DEFF Research Database (Denmark)

    Conradsen, Knut; Nielsen, Allan Aasbjerg; Skriver, Henning

    scattering matrix, and after suitable preprocessing the outcome at each picture element (pixel) may be represented as a 3 by 3 Hermitian matrix following a complex Wishart distribution. One approach to solving the change detection problem based on SAR images is therefore to apply suitable statistical tests...... holds a strong potential for change detection studies in remote sensing. In polarimetric synthetic aperture radar we measure the amplitude and phase of backscattered signals in four combinations of the linear horizontal and vertical receive and transmit polarizations. These signals form a complex...... in the complex Wishart distribution. We propose a set-up for a systematic solution to the (practical) problems using the likelihood ratio test statistics. We show some examples based on a time series of images with 1024 by 1024 pixels....

  6. AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Q. Zhao

    2016-06-01

    Full Text Available Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

  7. Geospatial Visualization of Global Satellite Images with Vis-EROS

    Energy Technology Data Exchange (ETDEWEB)

    Standart, G. D.; Stulken, K. R.; Zhang, Xuesong; Zong, Ziliang

    2011-04-13

    The Earth Resources Observation and Science (EROS) Center of U.S. Geological Survey is currently managing and maintaining the world largest satellite images distribution system, which provides 24/7 free download service for researchers all over the globe in many areas such as Geology, Hydrology, Climate Modeling, and Earth Sciences. A large amount of geospatial data contained in satellite images maintained by EROS is generated every day. However, this data is not well utilized due to the lack of efficient data visualization tools. This software implements a method for visualizing various characteristics of the global satellite image download requests. More specifically, Keyhole Markup Language (KML) files are generated which can be loaded into an earth browser such as Google Earth. Colored rectangles associated with stored satellite scenes are painted onto the earth browser; and the color and opacity of each rectangle is varied as a function of the popularity of the corresponding satellite image. An analysis of the geospatial information obtained relative to specified time constraints provides an ability to relate image download requests to environmental, political, and social events.

  8. Study on Geosynchronous Circular SAR

    Directory of Open Access Journals (Sweden)

    Hong Wen

    2015-06-01

    Full Text Available The concept of Geosynchronous Circular SAR (Geo-CSAR is introduced in this paper. With the design of the geosynchronous orbit parameters, a near-circular satellite sub-track could be formed to enable the staring imaging mode, which supports the advanced applications for wide-field and 3-D information acquisition under long-term consistent observation. This paper also analyzes Geo-CSAR's imaging formation capabilities, and concludes its attractive advantages over low-earth orbit spaceborne SAR in terms of instantaneous coverage, consistent observing area, 3-D positioning accuracy and etc.. Encouraging expectations for Geo-CSAR thus could be positively predicted in military investigation and disaster monitoring management applications.

  9. An Efficient SAR Image Segmentation Framework Using Transformed Nonlocal Mean and Multi-Objective Clustering in Kernel Space

    Directory of Open Access Journals (Sweden)

    Dongdong Yang

    2015-02-01

    Full Text Available Synthetic aperture radar (SAR image segmentation usually involves two crucial issues: suitable speckle noise removing technique and effective image segmentation methodology. Here, an efficient SAR image segmentation method considering both of the two aspects is presented. As for the first issue, the famous nonlocal mean (NLM filter is introduced in this study to suppress the multiplicative speckle noise in SAR image. Furthermore, to achieve a higher denoising accuracy, the local neighboring pixels in the searching window are projected into a lower dimensional subspace by principal component analysis (PCA. Thus, the nonlocal mean filter is implemented in the subspace. Afterwards, a multi-objective clustering algorithm is proposed using the principals of artificial immune system (AIS and kernel-induced distance measures. The multi-objective clustering has been shown to discover the data distribution with different characteristics and the kernel methods can improve its robustness to noise and outliers. Experiments demonstrate that the proposed method is able to partition the SAR image robustly and accurately than the conventional approaches.

  10. Restoration and enhancement of textural properties in SAR images using second-order statistics

    Science.gov (United States)

    Nezry, Edmond; Kohl, Hans-Guenther; De Groof, Hugo

    1994-12-01

    Local second order properties, describing spatial relations between pixels are introduced into the single-point speckle adaptive filtering processes, in order to account for the effects of speckle spatial correlation and to enhance scene textural properties in the restored image. To this end, texture measures originating, first from local grey level co-occurrence matrices (GLCM), and second from the local autocorrelation functions (ACF) are used. Results obtained on 3-look processed ERS-1 FDC and PRI spaceborne images illustrate the performance allowed by the introduction of these texture measures in the structure retaining speckle adaptive filters. The observable texture in remote sensing images is related to the physical spatial resolution of the sensor. For this reason, other spatial speckle decorrelation methods, more simple and easier to implement, for example post-filtering and linear image resampling, are also presented in this paper. In the particular case of spaceborne SAR imagery, all these methods lead to visually similar results. They produce filtered (radar reflectivity) images visually comparable to optical images.

  11. Multichannel and Wide-Angle SAR Imaging Based on Compressed Sensing

    Science.gov (United States)

    Sun, Chao; Wang, Baoping; Fang, Yang; Song, Zuxun; Wang, Shuzhen

    2017-01-01

    The multichannel or wide-angle imaging performance of synthetic aperture radar (SAR) can be improved by applying the compressed sensing (CS) theory to each channel or sub-aperture image formation independently. However, this not only neglects the complementary information between signals of each channel or sub-aperture, but also may lead to failure in guaranteeing the consistency of the position of a scatterer in different channel or sub-aperture images which will make the extraction of some scattering information become difficult. By exploiting the joint sparsity of the signal ensemble, this paper proposes a novel CS-based method for joint sparse recovery of all channel or sub-aperture images. Solving the joint sparse recovery problem with a modified orthogonal matching pursuit algorithm, the recovery precision of scatterers is effectively improved and the scattering information is also preserved during the image formation process. Finally, the simulation and real data is used for verifying the effectiveness of the proposed method. Compared with single channel or sub-aperture independent CS processing, the proposed method can not only obtain better imaging performance with fewer measurements, but also preserve more valuable scattering information for target recognition. PMID:28165433

  12. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

    Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

  13. Geodetic imaging: Reservoir monitoring using satellite interferometry

    Science.gov (United States)

    Vasco, D.W.; Wicks, C.; Karasaki, K.; Marques, O.

    2002-01-01

    Fluid fluxes within subsurface reservoirs give rise to surface displacements, particularly over periods of a year or more. Observations of such deformation provide a powerful tool for mapping fluid migration within the Earth, providing new insights into reservoir dynamics. In this paper we use Interferometric Synthetic Aperture Radar (InSAR) range changes to infer subsurface fluid volume strain at the Coso geothermal field. Furthermore, we conduct a complete model assessment, using an iterative approach to compute model parameter resolution and covariance matrices. The method is a generalization of a Lanczos-based technique which allows us to include fairly general regularization, such as roughness penalties. We find that we can resolve quite detailed lateral variations in volume strain both within the reservoir depth range (0.4-2.5 km) and below the geothermal production zone (2.5-5.0 km). The fractional volume change in all three layers of the model exceeds the estimated model parameter uncertainly by a factor of two or more. In the reservoir depth interval (0.4-2.5 km), the predominant volume change is associated with northerly and westerly oriented faults and their intersections. However, below the geothermal production zone proper [the depth range 2.5-5.0 km], there is the suggestion that both north- and northeast-trending faults may act as conduits for fluid flow.

  14. Bayesian Fusion of Multi-Scale Detectors for Road Extraction from SAR Images

    Directory of Open Access Journals (Sweden)

    Rui Xu

    2017-01-01

    Full Text Available This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR imagery for improving the accuracy of road extraction. The state-of-the-art approaches, such as fraction extraction and road network optimization, failed to obtain continuous road segments in separate successions, since the optimization could not change the parts ignored by the fraction extraction. In this paper, the proposed algorithm integrates the fraction extraction and optimization procedure simultaneously to extract the road network: (1 the Bayesian framework is utilized to transfer the road network extraction to joint reasoning of the likelihood of fraction extraction and the priority of network optimization; (2 the multi-scale linear feature detector (MLFD and the network optimization beamlet are introduced; (3 the conditional random field (CRF is used to reason jointly. The result is the global optimum since the fraction extraction and network optimization are exploited at the same time. The proposed algorithm solves the problem that the fractions are bound to reduce in the process of network optimization and has demonstrated effectiveness in real SAR images applications.

  15. Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm

    Science.gov (United States)

    Zhang, Siqian; Kuang, Gangyao

    2014-10-01

    In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.

  16. Expressway deformation mapping using high-resolution TerraSAR-X images

    KAUST Repository

    Shi, Xuguo

    2014-01-27

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  17. 卫星合成孔径雷达探测海底地形研究进展%Progress in Research of Satellite SAR Detection of Ocean Bottom Topography

    Institute of Scientific and Technical Information of China (English)

    郑全安; 谢玲玲

    2016-01-01

    Using satellite synthetic aperture radar (SAR)to detect ocean bottom topography is a challeng-ing problem for the research of ocean remote sensing physics and ocean dynamics.The reason is that radar pulses are unable to penetrate into seawater based on the principles of electromagnetic wave propagation, thus unable to detect ocean bottom topographic features directly.However,ocean bottom topographic fea-tures indeed show up on satellite SAR images in many cases.These topographic features are distributed not only in the shallow waters with depths shallower than 100 m,but also in the deep waters with depths deeper than 600~800 m and even 2000~3000 m.This paper overviews the frontier and progress in studies of this field.The key points include the fundamental theories for radar imaging of ocean surface processes, the SAR imaging theories for ocean bottom topographic features in three ocean areas:the Liaodong Shoal and the Taiwan Tan of China as well as the Gulf Stream region east of USA.The three cases represent lon-gitudinal shear flow passing over parallel ocean bottom topography,stratified traverse flow crossing over parallel (periodic)ocean bottom topography and strong ocean current passing over isolated ocean bottom topography.The theories and analysis methods derived from the three cases may serve as a baseline for in-terpretations of more complex cases and explorations of new application fields.%利用卫星合成孔径雷达(SAR)图像信息探测海底地形是海洋遥感物理学和海洋动力学研究具有挑战性的问题,这是因为根据电磁波传播原理,雷达脉冲没有能力穿透海水,因而不可能直接探测到海底地形特征,可是,许多卫星 SAR 图像上确实显示出海底地形特征。这些海底地形不仅分布在水深小于100 m 的浅海,而且在600~800 m 甚至2000~3000 m 的深海区也有发现。本文概略介绍该领域的发展前沿和研究进展,主要内容包括海面过程雷达成像基

  18. The best printing methods to print satellite images

    Directory of Open Access Journals (Sweden)

    G.A. Yousif

    2011-12-01

    In this paper different printing systems were used to print an image of SPOT-4 satellite, caver part of Sharm Elshekh area, Sinai, Egypt, on the same type of paper as much as possible, especially in the photography. This step is followed by measuring the experimental data, and analyzed colors to determine the best printing systems for satellite image printing data. The laser system is the more printing system where produce a wider range of color and highest densities of ink and access much color detail. Followed by the offset system which it recorded the best dot gain. Moreover, the study shows that it can use the advantages of each method according to the satellite image color and quantity to be produced.

  19. An Improved Phase Correlation Method for Obtaining Dynamic Feature of the Ocean from Sequential SAR Sub-aperture Images (in English

    Directory of Open Access Journals (Sweden)

    Wang Xiao-qing

    2013-03-01

    Full Text Available Dynamic features are important aspects of the ocean. However the dynamic information is lost in most conventional Synthetic Aperture Radar (SAR image processing methods, because they treat the image as an instantaneous state of the observed area. In fact, we can obtain dynamic features of the ocean from sequential sub-aperture images, because we know that the different parts of the azimuthal aperture correspond to different imaging instances. A key step for retrieving the dynamic features from sequential images is image-matching. However, the heavy noise characteristic of sub-aperture SAR images renders the traditional image-matching methods ineffective. In this paper we propose an image matching method based on improved phase correlation to deal with the heavy noise problem of SAR sub-aperture images. Experimental results show that the improved image-matching method presents an accuracy of 0.15 pixel and noise robustness. The analysis indicates that the improved algorithm is competent for obtaining dynamic information from the medium resolution airborne SAR images or high resolution spaceborne SAR images with 0.15-0.3 m/s estimation precision under most SNR conditions. The improved algorithm was used on an airborne SAR data to retrieve the movement velocity. The retrieved velocity ranged from 0.05-0.5 m/s, which seems to be reasonable value for the ocean current velocity.

  20. Vehicle Detection and Classification from High Resolution Satellite Images

    Science.gov (United States)

    Abraham, L.; Sasikumar, M.

    2014-11-01

    In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.