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  • Articles  (348)
  • 2010-2014  (348)
  • 2013  (348)
  • Geography  (348)
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  • Articles  (348)
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  • 2010-2014  (348)
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  • 1
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    An Improved Adaptive Intensity–Hue–Saturation Method for the Fusion of Remote Sensing Images (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2013-12-14
    Description: 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.
    Print ISSN: 1545-598X
    Electronic ISSN: 1558-0571
    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
    Published by Institute of Electrical and Electronics Engineers (IEEE)
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  • 2
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    Compressive Sensing-Based ISAR Imaging via the Combination of the Sparsity and Nonlocal Total Variation (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: 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.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 3
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    Markovian Change Detection of Urban Areas Using Very High Resolution Complex SAR Images (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: 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.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 4
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    Decomposition of the Kennaugh Matrix Based on a New Norm (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: In this letter, a new method for Kennaugh matrix decomposition is proposed, and a new norm for the Kennaugh matrix is defined. The Kennaugh matrix is decomposed into two parts: The first is a coherent target matrix, and the second is a residual matrix with minimum norm. The properties of the extracted coherent target are discussed, and an application of the extracted coherent target is implemented. In this application, an incoherent image is converted into a coherent image. Single-look sphere–diplane–helix decomposition is then performed. An experiment on Airborne SAR polarimetric data over San Francisco has been carried out, thus demonstrating the effectiveness of the application.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 5
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    Nonlinear Elastic Model for Flexible Prediction of Remotely Sensed Multitemporal Images (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: While an increasing number of satellite images are collected over a regular period in order to provide regular spatiotemporal information on land-use and land-cover changes, there are very few compression schemes in remotely sensed imagery that use historical data as a reference. Just as individual images can be compressed for separate transmission by taking into account their inherent spatial and spectral redundancies, the temporal redundancy between images of the same scene can also be exploited for sequential transmission. In this letter, we propose a nonlinear elastic method based on the general relationship to predict adaptively the current image from a previous reference image without any loss of information. The main feature of the developed method is to find the best prediction for each pixel brightness value individually using its own conditional probabilities to the previous image, instead of applying a single linear or nonlinear model. A codebook is generated to record the nonlinear point-to-point relationship. This temporal lossless compression is incorporated with spatial- and spectral-domain predictions, and the performances are compared with those of the JPEG2000 standard. The experimental results show an improved performance by more than 5%.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 6
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    A Comparative Study of Sea Clutter Covariance Matrix Estimators (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: Estimation of the polarimetric covariance matrix is an important task in statistical modeling of sea clutter for maritime applications of polarimetric synthetic aperture radar data. This letter provides a comprehensive study of four covariance matrix estimators: the maximum likelihood estimators under the Gaussian distribution (G-ML) and the K distribution (K-ML), an approximation of the latter (AK-ML), and a robust M-estimator. It adds to previous theoretical studies of these algorithms by evaluating their performance with respect to both estimation accuracy and computational efficiency. Experiments are performed on simulated data sets. Various texture conditions of the sea clutter are considered in the study.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 7
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    An Amplitude-Preserved Time–Frequency Peak Filtering Based on Empirical Mode Decomposition for Seismic Random Noise Reduction (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2013-12-14
    Description: 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.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 8
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    Hyperspectral Image Classification Based on Relaxed Clustering Assumption and Spatial Laplace Regularizer (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: 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.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 9
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    A SAR Image Registration Method Based on Pixel Migration of Edge-Point Feature (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: 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.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 10
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    Advances in $hbox{CO}_{2}$ Observations From AIRS and ACOS (2013)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2013-12-14
    Description: 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 $( hbox{CO}_{2})$ . Most recently, the Atmospheric $hbox{CO}_{2}$ Observations from Space (ACOS) project and GES DISC released $ hbox{CO}_{2}$ 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 $hbox{CO}_{2}$ from AIRS, as well as the most recent status of the total column-average distribution of $ hbox{CO}_{2}$ from ACOS. We also demonstrate that significant discrepancies still exist in the global distribution of observed and modeled column amounts of $hbox{CO}_{2}$ using the $hbox{CO}_{2}$ retrievals from the ACOS project.
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