- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Ratio-Based Multitemporal SAR Images Denoising: RABASAR
摘要： In this paper, we propose a fast and efficient multitemporal despeckling method. The key idea of the proposed approach is the use of the ratio image, provided by the ratio between an image and the temporal mean of the stack. This ratio image is easier to denoise than a single image thanks to its improved stationarity. Besides, temporally stable thin structures are well preserved thanks to the multitemporal mean. The proposed approach can be divided into three steps: 1) estimation of a 'superimage' by temporal averaging and possibly spatial denoising; 2) denoising of the ratio between the noisy image of interest and the 'superimage'; and 3) computation of the denoised image by remultiplying the denoised ratio by the 'superimage.' Because of the improved spatial stationarity of the ratio images, denoising these ratio images with a speckle-reduction method is more effective than denoising images from the original multitemporal stack. The amount of data that is jointly processed is also reduced compared to other methods through the use of the 'superimage' that sums up the temporal stack. The comparison with several state-of-the-art reference methods shows better results numerically (peak signal-noise-ratio and structure similarity index) as well as visually on simulated and synthetic aperture radar (SAR) time series. The proposed ratio-based denoising framework successfully extends single-image SAR denoising methods to time series by exploiting the persistence of many geometrical structures.
关键词： ratio image,speckle reduction,Multitemporal synthetic aperture radar (SAR) series,superimage
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Significant Wave Height Retrieval from Gaofen-3 Wave Mode Images
摘要： Significant wave height (Hs), is an important parameter, represented as the integration of directional wave spectra. Although many researchers have directly extracted Hs from SAR images and got a great accuracy of retrieval, those approaches are not suitable for GF-3 SAR data. In this paper, we propose an empirical approach for SAR Hs retrieval, using λc estimated from the real part of image cross spectra obtain from VV-polarized Gaofen-3 (GF-3) wave mode data acquired in different radar beams (called wave-code). Results using GF-3 wave mode data from January to February 2017 indicate that the bias and RMSE errors are: 189 wave-code, -0.13 m and 0.57 m; 190 wave-code, -0.07 m and 0.34 m; 193 wave-code, -0.3 m and 0.59 m; 199 wave-code, 0.16 m and 0.68 m; 215 wave-code, 0.2 m and 0.87 m. they show a relative behavior between the retrieved Hs and the Hs extracted from WAVEWATCH-III (WW3). However, there is a significant error when WW3-extracted Hs exceed 4 m. It seems that the model is not suitable for Hs retrieval on high sea conditions.
关键词： wave empirical retrieval,GF-3,cutoff wavelength estimation,synthetic aperture radar,wave mode
更新于2025-09-23 15:22:29
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An Online Multiview Learning Algorithm for PolSAR Data Real-Time Classification
摘要： Polarimetric synthetic aperture radar (PolSAR) data are sequentially acquired and usually large scale. Fast and accurate classification is particularly important for their applications. By introducing online learning, the PolSAR system can learn a classification model incrementally from a stream of instances, which is of high efficiency for newly arrived samples processing, strong adaptability for a dynamically changing environment, and excellent scalability for rapidly increasing data. In this paper, we propose an Online Multi-view Passive-Aggressive learning algorithm, named OMPA, for PolSAR data real-time classification. The polarimetric, color, and texture features are extracted to characterize PolSAR data, and each type of features corresponds to one view. In order to exploit the consistency and complementary property of these views, we give a new optimization model that ensembles the classifiers of multiple distinct views and enforces the agreement between each predictor and the combined predictor. The corresponding algorithms for both binary and multiclass classification tasks are derived, and the update steps have analytical solutions. In addition, we rigorously derive a bound on the number of prediction mistakes of the method. The proposed OMPA algorithm is evaluated on two real PolSAR datasets for built-up areas extraction and land cover classification, respectively. Experimental results demonstrate that OMPA consistently maintains a smaller mistake rate with low time cost and achieves about 1% and 2% accuracy improvements on the datasets, respectively, compared with the best results of the previously known online single-view and multiview learning methods.
关键词： polarimetric synthetic aperture radar (PolSAR),Multiview learning,passive-aggressive (PA) algorithm,online classification
更新于2025-09-23 15:22:29
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PolSAR Coherency Matrix Optimization Through Selective Unitary Rotations for Model-Based Decomposition Scheme
摘要： In this letter, a special unitary SU(3) matrix group is exploited for coherency matrix transformations to decouple the energy between orthogonal states of polarization. This decoupling results in the minimization of the cross-polarization power along with the removal of some off-diagonal terms of coherency matrix. The proposed unitary transformations are utilized on the basis of the underlying dominant scattering mechanism. By doing so, the reduced power from the cross-polarization channel is always concentrated on the underlying dominant co-polar scattering component. This makes it unique in comparison to state-of-the-art techniques. The proposed methodology can be adopted to optimize the coherency matrix to be used for the model-based decomposition methods. To verify this, pioneer three-component decomposition model is implemented using the proposed optimized coherency matrix of two different test sites. The comparative studies are analyzed to show the improvements over state-of-the-art techniques.
关键词： Coherency matrix,polarimetric synthetic aperture radar (PolSAR),cross-polarization,unitary matrix rotation,land-cover classification
更新于2025-09-23 15:22:29
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[IEEE 2018 OCEANS - MTS/IEEE Kobe Techno-Ocean (OTO) - Kobe, Japan (2018.5.28-2018.5.31)] 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO) - The 3D Imaging for Underwater Objects Using SAS Processing Based on Sparse Planar Array
摘要： Acoustic imaging of underwater objects has to include targets of two kinds which are unburied and buried, so that it can demonstrate the underwater environment thoroughly. Especially for the buried objects, it is much more difficult than unburied ones to obtain a qualified acoustical image due to the high backscattering reverberation generated by buried sediments. The three-dimensional downward-looking synthetic aperture sonar(SAS) imaging algorithm based on T-type sparse planar array is presented here to quantify and enhance the performance of underwater objects imaging and to improve the efficiency of sonar mapping as well. Pulse compression, multi narrow-beam nearfield beamforming and synthetic aperture method are applied in vertical direction, across-track direction and along-track direction, respectively. The simulation results show that with regard to the along-track direction, resolution is dependent on the length of the physical aperture and central frequency, as well as irrelevant to the range. Meanwhile, the signal-to-noise ratio(SNR) of image improves with the increase of the length of the synthetic aperture. The across-track direction resolution, however, degrades with the increase of the number of the along-track array elements. Moreover, the method is applied to the sea-trial data of shallow seawater area, where the depth of water is approximately 100 meters and the linear objects are buried at depth of about 3 meters. The results show that the presented algorithm is capable of leading the qualified imaging results for underwater targets.
关键词： underwater object imaging,downward-looking mode,nearfield beamforming,synthetic aperture processing
更新于2025-09-23 15:22:29
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[IEEE 2018 China International SAR Symposium (CISS) - Shanghai (2018.10.10-2018.10.12)] 2018 China International SAR Symposium (CISS) - Reconstruction Full-Pol SAR Data from Single-Pol SAR Image Using Deep Neural Network
摘要： Compared with single channel polarimetric (single-pol) SAR image, full polarimetric (full-pol) data convey richer information, but with compromises on higher system complexity and lower resolution or swath. In order to balance these factors, a deep neural networks based method is proposed to recover full-pol data from single-pol data in this paper. It consists of two parts: a feature extractor network is applied first to extract hierarchical multi-scale spatial features, followed by a feature translator network to predict polarimetric features with which full-pol SAR data can be recovered. Both qualitative and quantitative results show that the recovered full-pol SAR data agrees well with the real full-pol data. No prior information is assumed for scatterer media, and the framework can be easily expanded to recovery full-pol data from non-full-pol data. Traditional PolSAR applications such as model-based decomposition and unsupervised classification can now be applied directly to recovered full-pol SAR image to interpret the physical scattering mechanism.
关键词： synthetic aperture radar (SAR),deep neural network (DNN),polarimetric reconstruction
更新于2025-09-23 15:22:29
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[IEEE 2018 China International SAR Symposium (CISS) - Shanghai (2018.10.10-2018.10.12)] 2018 China International SAR Symposium (CISS) - A High Frequency Vibration Compensation Approach in Terahertz SAR Based on Wavelet Multi-Resolution Analysis
摘要： The use of terahertz wave in SAR imaging can solve the difficulties of frame rate and detection of slow moving targets in conventional SAR imaging. The most important difference between terahertz SAR (THz-SAR) and conventional SAR is the treatment on motion compensation. For reason that the wavelength of terahertz SAR is much shorter than that of conventional microwave SAR, the tiny vibration of SAR platform will blur SAR images, especially high frequency components. The high frequency vibration will result in paired echoes in SAR imaging, which can't be focused with traditional SAR imaging algorithms. Thus the vibration parameters can't be estimated precisely enough to construct the reference function to compensate the sinusoidal modulation phase. So we first get focused paired echoes in terahertz SAR imaging through Doppler keystone transform (DKT), then we propose a frequency estimation method based on wavelet multi-resolution analysis, along with parametric space projection method, to complete the high frequency vibration estimation of terahertz SAR. At last, the numerical tests using the point target echoes validate the proposed method.
关键词： synthetic aperture radar,high frequency vibration error,Terahertz,wavelet multi-resolution analysis,vibration estimation
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - Shenzhen, China (2018.7.13-2018.7.15)] 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - An Object-Based Method Based on a Novel Statistical Distance for SAR Image Change Detection
摘要： This paper introduces an object-based method based on a new statistical distance for SAR image change detection. Firstly, multi-temporal segmentation is carried out to segment two temporal SAR images simultaneously. It considers the homogeneity in two temporal images, and could generate homogeneous objects in spectral, spatial and temporal. In addition, through setting different segmentation parameters, the multi-temporal images can be segmented in a set of scales. This process exploits the advantages of OBIA that could effectively reduce spurious changes, and considers the scale of change detection task. Secondly, a multiplicative noise model called Nakagami–Rayleigh distribution is employed to describe SAR data, and then applied to Bayesian formulation. Thus, a new statistical distance that is insensitive to speckles is derived to measure the distances between pairs of parcels. Then, cluster ensemble algorithm is utilized to improve accuracy of individual result in each scale to obtain the final change detection map. Finally, multi-temporal Radarsat-2 images are employed to verify the effectiveness of the proposed method compared with other four methods.
关键词： synthetic aperture radar (SAR),multi-scale analysis,object-based image analysis,change detection
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Ultrasonics Symposium (IUS) - Kobe, Japan (2018.10.22-2018.10.25)] 2018 IEEE International Ultrasonics Symposium (IUS) - Feasibility Study of a Coherent Multi-Transducer US Imaging System
摘要： Ultrasound images can be difficult to assess, because of the limited resolution and view-dependent artefacts that are inherent to the small aperture transducers used clinically. An extended aperture has the potential to greatly improve imaging performance. This work introduces a fully coherent multi-transducer ultrasound imaging system, formed by two ultrasound transducers that are synchronized, freely located in space with a common field of view and transmit plane waves. Through coherent combination of the different transducers, a larger effective aperture is obtained and then an improved final image. First phantom images produced using this technique are presented here.
关键词： Large Aperture,Beamforming,Image Resolution,Plane Waves,Ultrasound Imaging
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Validation of SAR Iceberg Detection with Ground-Based Radar and GPS Measurements
摘要： Calving of icebergs at the tidewater glacier fronts is a component of the mass loss in Polar regions. Studying the regional distribution of icebergs, their volume, motion, and interaction with the environment is of interest. Here, we present the results from a fieldwork campaign conducted in Kongsfjorden, Svalbard in April 2016, where both satellite and ground-based remote sensing instruments were used to observe dynamics of sea ice, icebergs, and growlers. We used a ground-based radar system, imaging the study area every second minute during five days. During the same observation period, we collected four RADARSAT-2 (RS-2) quad-pol images, that are used for automatic detection of icebergs. In addition, the fieldwork team collected GPS positions of some drifting and grounded icebergs in the fjord to be used as ground-truth data. The comparison and combination of satellite, ground-based radar, and in-situ data contribute to cross-validate the results.
关键词： synthetic aperture radar,ground-based radar,polarimetry,GPS mapping,Iceberg,detection,sea ice
更新于2025-09-23 15:22:29