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Geoscience and Remote Sensing Letters, IEEE

Issue 5 • Date May 2014

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Displaying Results 1 - 25 of 33
  • [Front cover]

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Geoscience and Remote Sensing Letters publication information

    Page(s): C2
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  • Table of contents

    Page(s): 889 - 890
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  • Advances in $hbox{CO}_{2}$ Observations From AIRS and ACOS

    Page(s): 891 - 895
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1090 KB) |  | HTML iconHTML  

    NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes pioneering collections of data on atmospheric greenhouse gases. In September of 2012, the Atmospheric Infrared Sounder (AIRS) marked a decade of tropospheric observations of carbon dioxide (CO2). Most recently, the Atmospheric CO2 Observations from Space (ACOS) project and GES DISC released CO2 retrievals derived from radiances observed by the Japanese Greenhouse gases Observing SATellite (GOSAT) satellite, launched in 2009. In this letter, we present the most recent estimates of decadal mid-tropospheric trends of CO2 from AIRS, as well as the most recent status of the total column-average distribution of CO2 from ACOS. We also demonstrate that significant discrepancies still exist in the global distribution of observed and modeled column amounts of CO2 using the CO2 retrievals from the ACOS project. View full abstract»

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  • An Amplitude-Preserved Time–Frequency Peak Filtering Based on Empirical Mode Decomposition for Seismic Random Noise Reduction

    Page(s): 896 - 900
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1458 KB) |  | HTML iconHTML  

    Time-frequency peak filtering (TFPF) is a classical filtering method in time-frequency domain. It applies Wigner-Ville distribution to estimate the instantaneous frequency of an analytical signal. There is a pair of contradiction in this method, i.e., selecting a short window length may lead to good preservation for signal amplitude but bad random noise reduction whereas selecting a long window length may lead to serious attenuation for signal amplitude but effective random noise reduction. In order to make a good tradeoff between valid signal amplitude preservation and random noise reduction, we adopt empirical mode decomposition (EMD) to improve the TFPF results. The new idea is to utilize the decomposition characteristic of EMD which decomposes a signal to several modes from high to low frequency and to take advantage of the time-frequency filtering characteristic of TFPF which can recognize the valid signal component in the time-frequency plane in order to achieve effective random noise reduction together with good amplitude preservation. Through some experiments on synthetic seismic models and field seismic records, we show the better performance of the new method compared with the conventional TFPF. View full abstract»

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  • Hyperspectral Image Classification Based on Relaxed Clustering Assumption and Spatial Laplace Regularizer

    Page(s): 901 - 905
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (375 KB) |  | HTML iconHTML  

    In this letter, a relaxed clustering assumption and spatial Laplace-regularizer-based semisupervised hyperspectral image classifier is proposed. Considering the mixed pixels and noise intrinsic in hyperspectral image, we relax the clustering assumption employed in most of the available classifiers so that the similar hyperspectral vectors tend to share the “similar” labels instead of the “same” label, to formulate a modified spectral similarity regularizer. Moreover, the spatial homogeneity assumption is cast on hyperspectral pixels to construct a spatial regularizer, to overcome the salt-and-pepper misclassification of images. The effectiveness of our proposed method is evaluated via experiments on AVIRIS data, and the results show that it exhibits state-of-the-art performance, particularly when there are a small number of training samples. View full abstract»

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  • A SAR Image Registration Method Based on Pixel Migration of Edge-Point Feature

    Page(s): 906 - 910
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (326 KB) |  | HTML iconHTML  

    In this letter, a synthetic aperture radar (SAR) image registration method based on edge-point features is presented to improve precision, robustness, and applicability of SAR image registration. First, an affine transformation model is decomposed into six parameters with explicit geometric meanings. Next, based on the strength and direction features of the edge point, a matching similarity criterion and a joint similarity metric, i.e., the square summation joint feature, are constructed. Then, the parameters of the transformation model between SAR images are solved with a modified genetic algorithm that is able to get a global optimal solution of the metric. Finally, the performance of the proposed method is validated with two SAR image registration experiments. View full abstract»

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  • Adaptive Through-Wall Indication of Human Target with Different Motions

    Page(s): 911 - 915
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (991 KB) |  | HTML iconHTML  

    Through-wall indication of human targets is highly desired in many applications. Generally, human targets behind wall are noncooperative, and rare prior knowledge about the circumstance behind wall could be available. Thus, it requires the ability to indicate human targets with different motions from clutters. To investigate this problem, we first examine the conventional time-domain indication methods, and find that their performances are controlled by the historical pulse number adopted to estimate background, which corresponds to the tap-length from the angle of filter. Then, based on an intermittent mode of human target echoes, we define the optimum tap-length as the shortest tap-length that makes the filter output signal-to-clutter-and-noise ratio reach maximum and develop an adaptive indication method with a gradient tap-length control scheme to search the optimum tap-length. Finally, through-wall experiments with an impulse through-wall radar demonstrate that the proposed method can obtain a good adaptive indication performance on human target with different motions. View full abstract»

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  • Region-of-Interest Extraction Based on Frequency Domain Analysis and Salient Region Detection for Remote Sensing Image

    Page(s): 916 - 920
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (734 KB) |  | HTML iconHTML  

    Traditional approaches for detecting visually salient regions or targets in remote sensing images are inaccurate and prohibitively computationally complex. In this letter, a fast, efficient region-of-interest extraction method based on frequency domain analysis and salient region detection (FDA-SRD) is proposed. First, the HSI transform is used to preprocess the remote sensing image from RGB space to HSI space. Second, a frequency domain analysis strategy based on quaternion Fourier transform was employed to rapidly generate the saliency map. Finally, the salient regions are described by an adaptive threshold segmentation algorithm based on Gaussian Pyramids. Compared with existing models, the new algorithm is computationally more efficient and provides more visually accurate detection results. View full abstract»

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  • VecStatGraphs2D, A Tool for the Analysis of Two-Dimensional Vector Data: An Example Using QuikSCAT Ocean Winds

    Page(s): 921 - 925
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (620 KB) |  | HTML iconHTML  

    Circular or directional data are used in disciplines such as meteorology, geomatics, biology, and geology. The analysis of angular data requires special methods that are available in some statistical packages. However, these tools analyze only the angular values and do not include the vector modules, assuming unit vectors in all cases. In this letter, an open-source graphic and statistical package, i.e., VecStatGraphs2D, is described. It works in the R environment and provides statistics and graphics for modules (linear) and azimuths (circular), as well as graphics for the joint analysis of modules and azimuths. QuikSCAT satellite wind data are used to demonstrate some features of the package. QuikSCAT data are non-unit-length vectors, where both azimuth and magnitude (speed) are derived from u and v vector components (vector projections over the x- and y-axes). The example is used to show the seasonal change of winds in the Intertropical Convergence Zone, a key area in the ocean bird migration from the North to South Atlantic oceans. View full abstract»

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  • Interpolation-Free Stolt Mapping for SAR Imaging

    Page(s): 926 - 929
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (266 KB) |  | HTML iconHTML  

    Interpolation-free Stolt mapping, based on Fourier transform and phase multiplications, is proposed. Benefiting from this method, an efficient wavenumber domain algorithm (E-ω-k) can be achieved for generic synthetic aperture radar imaging. The method is finally demonstrated using simulated data. View full abstract»

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  • Contrast and Error-Based Fusion Schemes for Multispectral Image Pansharpening

    Page(s): 930 - 934
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (706 KB) |  | HTML iconHTML  

    The pansharpening process has the purpose of building a high-resolution multispectral image by fusing low spatial resolution multispectral and high-resolution panchromatic observations. A very credited method to pursue this goal relies upon the injection of details extracted from the panchromatic image into an upsampled version of the low-resolution multispectral image. In this letter, we compare two different injection methodologies and motivate the superiority of contrast-based methods both by physical consideration and by numerical tests carried out on remotely sensed data acquired by IKONOS and Quickbird sensors. View full abstract»

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  • Determination of Local Slope on the Greenland Ice Sheet Using a Multibeam Photon-Counting Lidar in Preparation for the ICESat-2 Mission

    Page(s): 935 - 939
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (657 KB) |  | HTML iconHTML  

    The greatest changes in elevation in Greenland and Antarctica are happening along the margins of the ice sheets where the surface frequently has significant slopes. For this reason, the upcoming Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission utilizes pairs of laser altimeter beams that are perpendicular to the flight direction in order to extract slope information in addition to elevation. The Multiple Altimeter Beam Experimental Lidar (MABEL) is a high-altitude airborne laser altimeter designed as a simulator for ICESat-2. The MABEL design uses multiple beams at fixed angles and allows for local slope determination. Here, we present local slopes as determined by MABEL and compare them to those determined by the Airborne Topographic Mapper (ATM) over the same flight lines in Greenland. We make these comparisons with consideration for the planned ICESat-2 beam geometry. Results indicate that the mean slope residuals between MABEL and ATM remain small ( 0.05 °) through a wide range of localized slopes using ICESat-2 beam geometry. Furthermore, when MABEL data are subsampled by a factor of 4 to mimic the planned ICESat-2 transmit-energy configuration, the results are indistinguishable from the full-data-rate analysis. Results from MABEL suggest that ICESat-2 beam geometry and transmit-energy configuration are appropriate for the determination of slope on ~ 90-m spatial scales, a measurement that will be fundamental to deconvolving the effects of surface slope from the ice-sheet surface change derived from ICESat-2. View full abstract»

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  • Classification of Very High Spatial Resolution Imagery Based on a New Pixel Shape Feature Set

    Page(s): 940 - 944
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1047 KB) |  | HTML iconHTML  

    This letter presents a novel spatial features extraction method for the high spatial resolution multispectral imagery (HSRMI) classification. First, Canny filter algorithm is applied to extract the edge information to obtain the fuzzy edge map. Secondly, adaptive threshold value for each pixel's homogeneous region (PHR) calculation is determined based on the fuzzy edge map and original image. Next, the PHR for every pixel is obtained based on the fuzzy edge map, adaptive threshold value and original image. And then, the pixel shape feature set (PSFS) is extracted based on the PHR. Lastly, SVM classifier is applied to classify the hybrid spectral and PSFS. Two different experiments were performed to evaluate the performance of PSFS, in comparison with spectral, gray level co-occurrence matrix (GLCM) and the existing pixel shape index (PSI). Experimental results indicate that the PSFS achieved the highest accuracy, hence, providing an effective spectral-spatial classification method for the HSRMI. View full abstract»

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  • Ocean Color Continuity From VIIRS Measurements Over Tampa Bay

    Page(s): 945 - 949
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (812 KB) |  | HTML iconHTML  

    Ocean color continuity calls for consistent observations from multiple sensors in order to establish a seamless data record to address earth science questions. Currently, both Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites are being operated well beyond their designed five-year mission life, and they have shown signs of sensor degradation. It is thus urgent to evaluate whether the most recently launched Visible Infrared Imager Radiometer Suite (VIIRS) instrument (2011 to present) can provide consistent observations should MODIS instruments stop functioning. In this study, the consistency between MODIS/Aqua and VIIRS measurements over the Tampa Bay estuary ( ~ 1000 km2) is assessed for remote sensing reflectance (Rrs, sr-1), chlorophyll-a concentrations (Chla, mg·m-3), and absorption coefficient of colored dissolved organic matter (ag(443), m-1). While Rrs was derived as a standard National Aeronautics and Space Administration product from the SeaDAS software package (reprocessing version R2013.0), Chla and ag(443) were estimated using the recently developed regional algorithms for Tampa Bay. Time-series analysis and statistics both showed that the two sensors provided consistent measurements for most products evaluated, with unbiased mean percentage differences of 25% and mean annual biases within -9% (except for one of the eight cases) for large dynamic ranges in Chla (1.0-20 mg·m-3) and ag(443) (0.1-1.5 m-1) in all four bay segments. These estimates are comparable or better than those derived from satellite-in situ comparisons, suggesting that VIIRS will provide observations consistent with MODIS, ensuring ocean color continuity and seamless data records for Tampa Bay. Such observations are crucial in establishing a long-term satellite-based water quality decision matrix for Tampa Bay. View full abstract»

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  • Identifying Man-Made Objects Along Urban Road Corridors From Mobile LiDAR Data

    Page(s): 950 - 954
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (963 KB) |  | HTML iconHTML  

    This letter is dedicated to a generic approach for the automated detection and classification of man-made objects in urban corridors from point clouds acquired by vehicle-borne mobile laser scanning (MLS). The approach is designed based on a priori knowledge in urban areas: 1) man-made objects feature geometric regularity such as vertical planar structures (e.g., building facades), whereas vegetation reveals huge diversity in shape and point distribution and 2) different types of urban man-made objects can be characterized by the point extension and the height above the ground level. Therefore, MLS-based point clouds are first divided into three layers with respect to the vertical height. In each layer, seed points of man-made objects are indicated by a line filter in the footprints of off-ground objects, which is generated by binarizing the spatial accumulation map of the point clouds. These seed points are further classified by examining in which layers the seed points of objects are found. Finally, points belonging to respective objects can be retrieved based on the classified seed points. The experiments show that various man-made objects on both sides of the street can be well detected, with a detection rate of up to 83%. For the classification of detected urban objects, overall accuracy of 92.37% can be achieved. View full abstract»

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  • Real-Time Implementation of the Pixel Purity Index Algorithm for Endmember Identification on GPUs

    Page(s): 955 - 959
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (673 KB) |  | HTML iconHTML  

    Spectral unmixing amounts to automatically finding the signatures of pure spectral components (called endmembers in the hyperspectral imaging literature) and their associated abundance fractions in each pixel of the hyperspectral image. Many algorithms have been proposed to automatically find spectral endmembers in hyperspectral data sets. Perhaps one of the most popular ones is the pixel purity index (PPI), which is available in the ENVI software from Exelis Visual Information Solutions. This algorithm identifies the endmembers as the pixels with maxima projection values after projections onto a large randomly generated set of random vectors (called skewers). Although the algorithm has been widely used in the spectral unmixing community, it is highly time consuming as its precision asymptotically increases. Due to its high computational complexity, the PPI algorithm has been recently implemented in several high-performance computing architectures, including commodity clusters, heterogeneous and distributed systems, field programmable gate arrays, and graphics processing units (GPUs). In this letter, we present an improved GPU implementation of the PPI algorithm, which provides real-time performance for the first time in the literature. View full abstract»

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  • SAR Image Filtering Based on the Cauchy–Rayleigh Mixture Model

    Page(s): 960 - 964
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (691 KB) |  | HTML iconHTML  

    In this letter, a novel maximum a posteriori (MAP) filter for synthetic aperture radar (SAR) images is developed. We characterize the return signal of SAR using the Cauchy-Rayleigh mixture model, which is an approximation to the heavy-tailed Rayleigh distribution. The parameters of the Cauchy-Rayleigh mixture model are estimated from the noisy observation by using the expectation-maximization algorithm. Finally, we compare the proposed filter with several classical spatial filtering techniques by applying them on simulated data and various real SAR images. Experimental results show that the Cauchy-Rayleigh-mixture-based MAP filter performs better for speckle removal than the other methods, including Lee, Kuan, and Γ-MAP. View full abstract»

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  • Parallax Correction in the Analysis of Multiple Satellite Data Sets

    Page(s): 965 - 969
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (510 KB) |  | HTML iconHTML  

    This letter describes a general solution to the parallax correction issue concerning the collocation of measurements of the same object from different satellites that use different viewing geometries. Two examples in cloud remote sensing are described with case studies. The applicability of the parallax correction is also discussed. Correct collocation of data collected by multiple satellites is needed in order to avoid introducing incorrect information in the data fusion of multiple sensors on different satellite platforms. View full abstract»

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  • Multichannel and Multiview Imaging Approach to Building Layout Determination of Through-Wall Radar

    Page(s): 970 - 974
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1301 KB) |  | HTML iconHTML  

    This letter considers the problem of building layout determination using through-wall-radar imaging technology, which employs multiple transmit-receive channels to implement multiview synthetic aperture imaging. In each view, the phase errors of multichannel data introduced by the unknown walls deteriorate significantly the performance of the coherently data-combined algorithm by Le Herein, we first obtain multiple single-channel building layout images for all independent channels of each view and propose a novel noncoherent fusion method named multiply-subtract-add to combine them into a single-view layout image. Then, we present an M- N- K detector plus median filtering to fuse multiple single-view layout images and reduce the existing cavities and burrs of wall images. The experimental results reveal that the presented noncoherent image fusion method gives the single-view layout images with higher signal-to-clutter-and-noise ratio than the conventional coherent algorithm based on data combination and a near-tidy panorama layout image is generated almost without the cavities and burrs. View full abstract»

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  • A Principal Component Based Haze Masking Method for Visible Images

    Page(s): 975 - 979
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (753 KB) |  | HTML iconHTML  

    Land surfaces are commonly obstructed by haze in remote sensing images, which reduces the available land cover information. Haze detection is therefore important for locating, avoiding, or restoring hazy regions. In this letter, a principal component (PC)-based haze masking (PCHM) method is developed for the masking of haze in visible remote sensing images covering land surfaces at middle latitudes. Owing to the evidence of haze in the second PC, the PCHM method results in accurate haze masks. The complete procedure comprises two steps: haze construction and spatial optimization. The validity of the PCHM method is demonstrated through its application to several hazy visible images clipped from Landsat Enhanced Thematic Mapper Plus scenes. The quantitative assessments verify the superiority of the proposed method over the haze optimized transformation method for the production of binary haze masks. In addition, the resulting haze masks are compared with a MODIS cloud product, which further proves the necessity and validity of the proposed method. View full abstract»

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  • Hyperspectral Imagery Classification Based on Rotation-Invariant Spectral–Spatial Feature

    Page(s): 980 - 984
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1119 KB) |  | HTML iconHTML  

    In this letter, we present a novel approach for spectral-spatial classification in hyperspectral imagery. After applying principal component (PC) analysis for dimensionality reduction, we extract the spectral-spatial information by first reorganizing the local image patch with the first d PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Since no additional operation except sorting the pixels is required, this step is performed efficiently. Afterward, the resulting feature descriptors are embedded into a linear support vector machine for classification. To evaluate the proposed method, experiments are preformed on two hyperspectral images with high spatial resolution. The experimental results confirm that the proposed method outperforms the existing algorithms on classification accuracy. View full abstract»

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  • An Improved Adaptive Intensity–Hue–Saturation Method for the Fusion of Remote Sensing Images

    Page(s): 985 - 989
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (733 KB) |  | HTML iconHTML  

    Extending on the adaptive intensity-hue-saturation (AIHS) method, an improved AIHS (IAIHS) method is proposed for pansharpening in this letter. Through the IAIHS method, the amount of spatial details injected into each band of the multispectral (MS) image is appropriately determined by a weighting matrix, which is defined on the basis of the edges of the panchromatic and MS images and the proportions between the MS bands. Experiments carried out on QuickBird and IKONOS satellite images show that the IAIHS method can maintain spectral quality while providing comparable spatial quality with the AIHS and additive wavelet luminance proportional methods. View full abstract»

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  • Compressive Sensing-Based ISAR Imaging via the Combination of the Sparsity and Nonlocal Total Variation

    Page(s): 990 - 994
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (484 KB) |  | HTML iconHTML  

    The sparsity of targets intrinsically paves a new way to apply compressive sensing (CS) to inverse SAR (ISAR) imaging. However, in the CS-based ISAR imaging system, the ISAR image is considered as a vector composed of random and independent scattering points, and the dependence between pixels is ignored, which always results in the degradation of the shape and geometry of targets, especially when the number of CS measurements and the signal-to-noise ratio are small. In this letter, a novel ISAR imaging framework is proposed via a combination of local sparsity constraint and nonlocal total variation (NLTV). The sparsity is a form prior that the number of strong scattering points is smaller than that of pixels in the image plane. It plays the role of classification of the strong scattering point from the clutter background. NLTV aims to suppress the noise and to remove some false strong scattering centers or clutter and simultaneously preserves the shape and geometry of target regions. Experiments on real data confirm the proposed method's validity. View full abstract»

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  • Markovian Change Detection of Urban Areas Using Very High Resolution Complex SAR Images

    Page(s): 995 - 999
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (786 KB) |  | HTML iconHTML  

    In this letter, an innovative technique for change detection in urban areas using very high resolution synthetic aperture radar multichannel stacks is proposed. Instead of using the amplitude image, as in classical change detection approaches, the proposed technique uses the full complex image in a Markovian framework. The complex data are modeled using Markov random field hyperparameters, which are particular local parameters that take into account the spatial correlation between pixels. Starting from two data sets, the pre- and the postevent ones, the proposed algorithm, first, estimates the two hyperparameter maps and, then, compares the similarity between them. If a change occurs between the pre- and the postevent acquisitions, the statistical distribution of the hyperparameter maps will change. The maximum distance between the two obtained statistical distributions provides an index of changes. This sort of spatial correlation maps is computed using statistical estimation techniques, while the similarity comparison is computed using the two-step Kolmogorov-Smirnov statistic test. The algorithm is validated on simulated data and tested on real COSMO-SkyMed data acquired on the area of Naples, showing interesting and promising results. View full abstract»

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Aims & Scope

IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts.

 

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Meet Our Editors

Editor-in-Chief
Alejandro C. Frery
Universidade Federal de Alagoas