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  • Articles  (1,190)
  • 2010-2014  (1,190)
  • Geography  (1,190)
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  • Articles  (1,190)
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  • 11
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    Three-Dimensional Sparse Turntable Microwave Imaging Based on Compressive Sensing (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: In this letter, we propose a fast reconstruction algorithm for 3-D turntable microwave imaging from sparse measurements. A conventional Fourier-transform-based 3-D microwave imaging method collects data over densely azimuth–elevation samples and needs a large amount of data storage and long collection time. To reduce the cost of data acquisition, the proposed method exploits the sparsity in the image domain to achieve 3-D microwave imaging by utilizing sparse measurements. For this aim, the signal model is first represented as a tensor array, and then, a novel sparse reconstruction algorithm called 3-D-SL0 is applied to recover the 3-D scattering reflectivity, i.e., a 3-D image. Simulation results are finally shown to investigate the validity of the proposed method.
    Print ISSN: 1545-598X
    Electronic ISSN: 1558-0571
    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 12
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    Characterization of Low-Backscatter Ocean Features in Dual-Copolarization SAR Using Log-Cumulants (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: The potential of using log-cumulants for discrimination between mineral oil spills and other low-backscatter ocean features in synthetic aperture radar data is investigated here. Radarsat-2 fine quad-polarization data containing experimental oil spills, as well as simulated biogenic slicks and a natural phenomenon, are analyzed. For this data set, the combined information of matrix log-cumulants of first and second order is found to clearly discriminate the majority of the mineral oil spills from the simulated biogenic slicks and the natural phenomenon. These preliminary findings suggest that the proposed method has a potential application in classification of low-backscatter ocean features of unknown origin.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 13
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    An Adaptive Pixon Extraction Technique for Multispectral/Hyperspectral Image Classification (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: Hyperspectral imaging has gained significant interest in the past few decades, particularly in remote sensing applications. The considerably high spatial and spectral resolution of modern remotely sensed data often provides more accurate information about the scene. However, the complexity and dimensionality of such data, as well as potentially unwanted details embedded in the images, may act as a degrading factor in some applications such as classification. One solution to this issue is to utilize the spatial–spectral features to extract segments before the classification step. This preprocessing often leads to better classification results and a considerable decrease in computational time. In this letter, we propose a Pixon-based image segmentation method, which benefits from a preprocessing step based on partial differential equation to extract more homogenous segments. Moreover, a fast algorithm has been presented to adaptively tune the required parameters used in our Pixon-based schema. The acquired segments are then fed into the support vector machine classifier, and the final thematic class maps are produced. Experimental results on multi/hyperspectral data are encouraging to apply the proposed Pixons for classification.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 14
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    Background Suppression and Strong Phase Codes in Incoherent Scatter Lag Profile Inversion (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: High range resolution incoherent scatter spectra are routinely measured by means of alternating codes and random codes. These radar transmission modulations are cycles of phase-coded pulses whose lagged products form complementary code sets, enabling decoding of incoherent scatter lag profiles by means of matched filtering. Numerically optimized near-perfect modulations are potential successors of the alternating codes and random codes because they enable new measurement techniques, such as so-called multipurpose experiments. The near-perfect modulations cannot be decoded by means of matched filtering, but they are designed for analysis by means of lag profile inversion. Two improvements to this combination are introduced in this letter: Suppression of background noise correlations is implemented as part of lag profile inversion, removing the need for dedicated background measurements, and the concept of strong phase codes is adopted to near-perfect modulations, allowing one to neglect the receiver impulse response in lag profile inversion.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 15
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    Effect of Land-Cover Type on the SMAP Active/Passive Soil Moisture Downscaling Algorithm Performance (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-12-06
    Description: A brightness temperature ( $hbox{Tb}$ ) downscaling algorithm based on the synergy between active and passive microwave observations is tested using airborne data that simulate the Soil Moisture Active Passive (SMAP) mission of the National Aeronautics and Space Administration scheduled for launch in January 2015. While this algorithm has been adopted as the baseline for SMAP, it has only been tested on a limited variety of land uses and vegetation types. Consequently, this study evaluates the SMAP active/passive downscaling algorithm using data with varied conditions. The SMAP experiment conducted in Australia has been used for this purpose. The algorithm was applied over several 9 km $times$ 9 km pixels with different land covers, so as to evaluate the accuracy of this algorithm under different heterogeneity levels. Brightness temperatures were downscaled from 9 to 3 km (approximating the resolution ratio of SMAP downscaling approach) across nine days of data. Results show that the root-mean-square error of $hbox{Tb}$ in grassland could meet the 2.4-K target accuracy of SMAP, while in cropping, it was 2 K higher than the target. The influence from water bodies was also assessed and confirmed to have a significant impact if not removed prior to downscaling.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 16
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    Weakly Supervised Learning for Target Detection in Remote Sensing Images (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2014-11-05
    Description: In this letter, we develop a novel framework of leveraging weakly supervised learning techniques to efficiently detect targets from remote sensing images, which enables us to reduce the tedious manual annotation for collecting training data while maintaining the detection accuracy to large extent. The proposed framework consists of a weakly supervised training procedure to yield the detectors and an effective scheme to detect targets from testing images. Comprehensive evaluations on three benchmarks which have different spatial resolutions and contain different types of targets as well as the comparisons with traditional supervised learning schemes demonstrate the efficiency and effectiveness of the proposed framework.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 17
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    Joint Sparsity Model for Multilook Hyperspectral Image Unmixing (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2014-11-05
    Description: Recent work on hyperspectral image (HSI) unmixing has addressed the use of overcomplete dictionaries by employing sparse models. In essence, this approach exploits the fact that HSI pixels can be associated with a small number of constituent pure materials. However, unlike traditional least-squares-based methods, sparsity-based techniques do not require a preselection of endmembers and are thus able to simultaneously estimate the underlying active materials along with their respective abundances. In addition, this perspective has been extended so as to exploit the spatial homogeneity of abundance vectors. As a result, these techniques have been reported to provide improved estimation accuracy. In this letter, we present an alternative approach that is able to relax, yet exploit, the assumption of spatial homogeneity by introducing a model that captures both similarities and differences between neighboring abundances. In order to validate this approach, we analyze our model using simulated as well as real hyperspectral data acquired by the HyMap sensor.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 18
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    Scaling Transform Method for Remotely Sensed FAPAR Based on FAPAR-P Model (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2014-11-05
    Description: Climate and land–atmosphere models rely on accurate land-surface parameters, such as the fraction of absorbed photosynthetically active radiation (FAPAR). It is known that FAPAR values retrieved from remote-sensing images suffer from scaling effects. Scaling transformation aims to derive accurate FAPAR values at a specific scale from values at other scales. In this letter, the scaling-effect mechanism and the scale-transformation algorithm are derived using a Taylor series expansion method based on the FAPAR model based on $P$ after simplification. The scaling algorithm was validated in the Heihe River Basin. The multiscale FAPAR values are inverted from 5-, 50-, and 100-m hyperspectral reflectance data. The scale-transformation formula was used, and the results agreed well with actual values.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 19
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    Training Sample Selection for Space-Time Adaptive Processing in Heterogeneous Environments (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2014-11-05
    Description: As training samples are not always identically distributed with the clutter in the cell under test (CUT) in heterogeneous environments, the estimated clutter covariance matrix for space-time adaptive processing (STAP) is not accurate, which degrades the performance of STAP. To improve the performance of STAP in heterogeneous environments, this letter proposes a novel training sample selection algorithm to estimate the covariance matrix. Based on the subaperture smoothing techniques, subapertures' covariance matrices are estimated, which are used to measure the similarities between the clutter covariance matrix of the CUT and the clutter covariance matrices of the training samples. Training samples whose clutter covariance matrices are similar to that of the CUT are selected, leading to a better estimation of the clutter covariance matrix, and the performance of STAP improves. Experimental results confirm the performance of the proposed algorithm.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
    Published by Institute of Electrical and Electronics Engineers (IEEE)
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  • 20
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    A Robust Delaunay Triangulation Matching for Multispectral/Multidate Remote Sensing Image Registration (2014)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2014-11-05
    Description: A novel dual-graph-based matching method is proposed in this letter particularly for the multispectral/multidate images with low overlapping areas, similar patterns, or large transformations. First, scale invariant feature transform based matching is improved by normalizing gradient orientations and maximizing the scale ratio similarity of all corresponding points. Next, Delaunay graphs are generated for outlier removal, and the candidate outliers are selected by comparing the distinction of Delaunay graph structures. In order to bring back the inliers removed in Delaunay triangulation matching iterations and to exclude the remaining outliers, the recovery strategy equipped with the dual graph of Delaunay is explored. Inliers located in the corresponding Voronoi cells are recovered to the residual sets. The experimental results demonstrate the accuracy and robustness of the proposed algorithm for various representative remote sensing images.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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