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Geoscience and Remote Sensing Letters, IEEE

Issue 3 • Date July 2010

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Displaying Results 1 - 25 of 49
  • [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): 419 - 420
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  • Denoising Satellite Gravity Signals by Independent Component Analysis

    Page(s): 421 - 425
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    Independent component analysis (ICA) is a blind separation method based on simple assumptions of the independence of sources and the non-Gaussianity of observations. An approach based on ICA is used here to extract hydrological signals over land and oceans from the polluting striping noise due to orbit repetitiveness and present in the gravity anomalies detected by the Gravity Recovery and Climate Experiment (GRACE) satellites. We took advantage of the availability of monthly level-2 GRACE solutions from three official providers (i.e., CSR, JPL, and GFZ) that can be considered as different observations of the same phenomenon. The efficiency of the methodology is demonstrated on a synthetic case. Applied to one month of GRACE solutions, it allows for clearly separating the total water storage change from the meridional-oriented spurious gravity signals on the continents but not on the oceans. This technique gives results equivalent to the destriping method for continental water storage. View full abstract»

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  • Spatial–Temporal Variability of Great Slave Lake Levels From Satellite Altimetry

    Page(s): 426 - 429
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (313 KB) |  | HTML iconHTML  

    The study of lake-level variability of five selected areas across Great Slave Lake (GSL) using satellite altimetry is presented. Data from Topex/Poseidon (TP) and Jason-1 (J1) missions at GSL for the ice-free seasons of 1993-2002 and 2002-2008, respectively, reveal lower performance of J1 for areas closer to 20 km from the coastline compared to 10 km for TP. A calculated bias of 6.99 cm was subtracted to J1 range since TP has better tracking of shoreline waters and lower data rejection. High correlation coefficients for the relative rate of change between lake altimetry heights (LAHs) and corresponding gauge data for Yellowknife Bay and Hay River support the use of LAH changes as effective indicators of variability at GSL. Differences in LAH between the five areas indicate a nonuniform slope which we relate more to variability of the surface water temperature distribution than wind effects. The deeper and colder areas are associated to the least change of LAH gradient through time; therefore, they represent ideal areas to study interannual climate variability. A potential correlation between areas with higher variability in LAH gradients and higher changes in modeled surface water temperatures during the 2003 ice free season is observed. View full abstract»

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  • Scaling the 3-D Image of Spinning Space Debris via Bistatic Inverse Synthetic Aperture Radar

    Page(s): 430 - 434
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (298 KB) |  | HTML iconHTML  

    In 3-D inverse synthetic aperture radar (ISAR) imaging of spinning space debris, the image obtained via the available algorithm is modified by a scaling factor. Determined by the angle between the spinning vector and the radar line of sight, this factor cannot be estimated by a monostatic radar in a short imaging interval. This letter derives the bistatic ISAR (Bi-ISAR) geometry and signal model for 3-D imaging of space debris. Then, a 3-D image scaling algorithm is introduced based on the connections between the mono- and bistatic echoes of the same scatterer. Numeric simulations have proved the validity of the proposed algorithm. View full abstract»

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  • Simultaneous Observation of Lunar Radar Sounder and Laser Altimeter of Kaguya for Lunar Regolith Layer Thickness Estimate

    Page(s): 435 - 439
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (335 KB) |  | HTML iconHTML  

    Simultaneous observations of Lunar Radar Sounder (LRS) and Laser ALTimeter (LALT) of Kaguya, a Japanese lunar exploration project, were carried out for the purpose of mapping regolith layer thickness of the Moon. Nadir surface echo of a high-frequency (5 MHz) pulse of LRS interferes the shallow (<; 10 m) subsurface echo from the bottom of the regolith layer, which subsequently makes the apparent surface be detected at a range deviated from the actual surface range, while the actual surface range is optically detected by LALT. Regolith layer thickness information is retrieved from this range difference after an inversion process. So far, four major maria on the near side of the Moon (Maria Tranquillitatis, Serenitatis, Imbrium, and Oceanus Procellarum) have been investigated, and the mean regolith layer thicknesses of the four maria were found to be about the same, ranging from 6.3 to 6.9 m. However, spatial distribution of areal regolith thickness appears different in eastern maria from western maria, which implies a difference of the growth history of the regolith layer. View full abstract»

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  • NPOESS Precipitation Retrievals Using the ATMS Passive Microwave Spectrometer

    Page(s): 440 - 444
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (932 KB) |  | HTML iconHTML  

    This letter evaluates the ability of the U.S. National Polar-orbiting Operational Environmental Satellite System 22-channel Advanced Technology Microwave Sounder (ATMS) to retrieve surface precipitation rates (millimeters per hour); water path estimates for rain, snow, and graupel (millimeters); and peak vertical wind (convective strength, meters per second). Simulated retrieval accuracies for ATMS were compared to those for its predecessor the Advanced Microwave Sounding Unit (AMSU), both of which sample the 23- to 190-GHz spectrum. ATMS retrieves all precipitation parameters up to ~ 25% more accurately than AMSU except for cloud ice and snow water paths, which are comparable. Image sharpening of the ATMS Nyquist-sampled observations below 90 GHz further improves the recovery of small features but amplifies noise so that the benefits are restricted primarily to finely structured convective systems. View full abstract»

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  • Three-Dimensional Imaging via Wideband MIMO Radar System

    Page(s): 445 - 449
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (276 KB) |  | HTML iconHTML  

    The 3-D inverse synthetic aperture radar imaging fast maneuvering targets is an active research area in the past decades. Planar antenna arrays are used to avoid the motion compensation algorithms but at the cost of increasing the hardware complexity. In this letter, to reduce the hardware complexity of the imaging system, a wideband multiple-input multiple-output system with two perpendicular linear arrays is suggested. In contrast to the existing 3-D imaging methods with planar antenna arrays, with the proposed method, the lower hardware complexity is achieved by many additive virtual array elements. Simulations based on synthetic data are provided for testing the proposed method. View full abstract»

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  • Motion Parameter Estimation in the SAR System With Low PRF Sampling

    Page(s): 450 - 454
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (407 KB) |  | HTML iconHTML  

    A novel approach to motion parameter estimation with low pulse repetition frequency (PRF) sampling based on compressed sensing (CS) theory is introduced. As is known to us, when PRF is less than the Doppler spectrum bandwidth, moving targets suffer both Doppler centroid frequency ambiguity and Doppler spectrum ambiguity. Under this condition, the traditional parameter estimation method in the Doppler domain is out of action. The key of this letter converts motion parameter estimation in the synthetic aperture radar system with low PRF sampling into solving an optimization equation based on CS theory. Because moving targets in the scene can be regarded as sparse signals after clutter cancellation, an optimization algorithm based on CS theory is proposed to reconstruct sparse signals and meanwhile estimate the along-track velocities and azimuth positions of moving targets. Considering the fact that range cell migration of moving targets is not subject to PRF limitations, Radon transform is adopted to obtain unambiguous across-track velocities and range positions. Results on simulation and real data are provided to show the effectiveness of this method. View full abstract»

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  • Mixture Analysis by Multichannel Hopfield Neural Network

    Page(s): 455 - 459
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (392 KB) |  | HTML iconHTML  

    Due to the spatial-resolution limitation, mixed pixels containing energy reflected from more than one type of ground objects are widely present in remote sensing images, which often results in inefficient quantitative analysis. To effectively decompose such mixtures, a fully constrained linear unmixing algorithm based on a multichannel Hopfield neural network (MHNN) is proposed in this letter. The proposed MHNN algorithm is actually a Hopfield-based architecture which handles all the pixels in an image synchronously, instead of considering a per-pixel procedure. Due to the synchronous unmixing property of MHNN, a noise energy percentage (NEP) stopping criterion which utilizes the signal-to-noise ratio is proposed to obtain optimal results for different applications automatically. Experimental results demonstrate that the proposed multichannel structure makes the Hopfield-based mixture analysis feasible for real-world applications with acceptable time cost. It has also been observed that the proposed MHNN-based mixture-analysis algorithm outperforms the other two popular linear mixture-analysis algorithms and that the NEP stopping criterion can approach optimal unmixing results adaptively and accurately. View full abstract»

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  • Covariance Statistics of Fully Polarimetric Brightness Temperature Measurements

    Page(s): 460 - 463
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (331 KB) |  | HTML iconHTML  

    The covariance statistics of measurements by a fully polarimetric microwave radiometer are derived using a fundamental noise-theoretic approach. Previous published derivations of a similar nature have only included the third Stokes brightness temperature. The results are confirmed by a series of numerical Monte Carlo simulations of the underlying radiometric measurement process. It is found that the additive noise that is present in the measurements can be correlated between polarimetric channels and that the correlation statistics will vary as a function of the polarization state of the scene under observation. General expressions are also derived for the measurement precision (the radiometric NEΔT) and the system noise temperature of the third and fourth Stokes channels. It is found that both the precision and noise temperature can also depend on the polarization state of the scene. View full abstract»

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  • Gaussian Process Regression for Estimating Chlorophyll Concentration in Subsurface Waters From Remote Sensing Data

    Page(s): 464 - 468
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    In this letter, we explore the effectiveness of a novel regression method in the context of the estimation of biophysical parameters from remotely sensed imagery as an alternative to state-of-the-art regression methods like those based on artificial neural networks and support vector machines. This method, called Gaussian process (GP) regression, formulates the learning of the regressor within a Bayesian framework, where the regression model is derived by assuming the model variables follow a Gaussian prior distribution encoding the prior knowledge about the output function. One of its interesting properties, which gives it a key advantage over state-of-the-art regression methods, is the possibility to tune the free parameters of the model in an automatic way. Experiments were focused on the problem of estimating chlorophyll concentration in subsurface waters. The achieved results suggest that the GP regression method is very promising from both viewpoints of estimation accuracy and free parameter tuning. Moreover, it handles particularly well the problem of limited availability of training samples, typically encountered in biophysical parameter estimation applications. View full abstract»

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  • A Kernel-Based Nonparametric Regression Method for Clutter Removal in Infrared Small-Target Detection Applications

    Page(s): 469 - 473
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    Small-target detection in infrared imagery with a complex background is always an important task in remote-sensing fields. Complex clutter background usually results in serious false alarm in target detection for low contrast of infrared imagery. In this letter, a kernel-based nonparametric regression method is proposed for background prediction and clutter removal, furthermore applied in target detection. First, a linear mixture model is used to represent each pixel of the observed infrared imagery. Second, adaptive detection is performed on local regions in the infrared image by means of kernel-based nonparametric regression and two-parameter constant false alarm rate (CFAR) detector. Kernel regression, which is one of the nonparametric regression approaches, is adopted to estimate complex clutter background. Then, CFAR detection is performed on “pure” target-like region after estimation and removal of clutter background. Experimental results prove that the proposed algorithm is effective and adaptable to small-target detection under a complex background. View full abstract»

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  • Modeling Envisat RA-2 Waveforms in the Coastal Zone: Case Study of Calm Water Contamination

    Page(s): 474 - 478
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (701 KB) |  | HTML iconHTML  

    Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This letter examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10-km2 island in the northwestern Mediterranean). Forty-six repeat passes were analyzed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly, one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modeling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges but also greatly enhance the study of storm surges and other coastal phenomena. View full abstract»

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  • HF Radio-Frequency Interference Mitigation

    Page(s): 479 - 482
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (788 KB) |  | HTML iconHTML  

    The dense radio-frequency interference (RFI) distributed on the spectrum in the high-frequency band greatly degrades the performance of radio systems and makes it urgent to find an effective and speedy method to eliminate the interferences. The interference mitigation method introduced in this letter is implemented before any further signal processing. It reconstructs the interference by the exactly estimated frequency, amplitude, and phase parameters in the signal spectrum and then subtracts the artificial interference from the input time-domain complex signal. The procedure steps of the method are illustrated in detail. The data stream of continuous oblique-incident ionospheric detection has been processed effectively and rapidly in real time. Several delay-Doppler ionograms severely contaminated by RFI are selected and presented. Comparisons of the original and mitigated ionograms and the signal-to-noise ratio (SNR) data show that the RFIs are eliminated perfectly and that the SNR is greatly improved. View full abstract»

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  • A New Method of Deriving Spectrum for Bistatic SAR Processing

    Page(s): 483 - 486
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (285 KB) |  | HTML iconHTML  

    The formulation of a point target spectrum is a key step in deriving synthetic aperture radar focusing algorithms, which exploits the processing efficiency of the frequency domain. However, the existence of a double-square root in the bistatic range equation makes it difficult to find an exact analytical solution for the 2-D spectrum. In this letter, according to the idea of function optimal approach, we derive a new 2-D point target spectrum on the basis of Legendre polynomial expansion, which is more exact than the existing spectra during the synthetic aperture time. View full abstract»

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  • Complex Permittivity Measurements of Rainwater in the 0.5–26.5 GHz Frequency Range

    Page(s): 487 - 490
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (238 KB) |  | HTML iconHTML  

    Modeling electromagnetic wave propagation in rain requires knowledge of the complex permittivity of rainwater. In response, we measured the complex permittivity of rainwater in the 0.5-26.5 GHz frequency range using an Agilent Technologies 85070E Dielectric Probe Kit and an Agilent N5242A-400 Vector Network Analyzer. Rainwater samples were collected in Graz (Austria) and Kototabang (Indonesia). The results obtained were found to differ slightly from those of Ray's and Liebe's models. However, the difference in the complex permittivity of rainwater between the measurement and model results exhibits very small biases in the Mie extinction coefficients ( <; 0.01%). View full abstract»

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  • Remote Sensing Image Registration Based on Retrofitted SURF Algorithm and Trajectories Generated From Lissajous Figures

    Page(s): 491 - 495
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (598 KB) |  | HTML iconHTML  

    In this letter, we propose a novel remote sensing image registration method by optimizing the Speeded Up Robust Features (SURF) and developing a new similarity measure function based on trajectories generated from Lissajous figures. Compared with SURF which has a low feature-matching rate in some complex cases, the retrofitted SURF algorithm is more robust and accurate. The algorithm greatly improves the correct matching rate to over 80%. Furthermore, the recognition capability of the similarity measure is enhanced by using a trajectory disturbance strategy, which is a significant displacement in the trajectory induced by a minor error of the transformation parameters. Experiments show the promising performance of the proposed image registration method. View full abstract»

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  • RF Tomography for Below-Ground Imaging of Extended Areas and Close-in Sensing

    Page(s): 496 - 500
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (332 KB) |  | HTML iconHTML  

    Three extensions to radio-frequency (RF) tomography for imaging of voids under wide areas of regard are presented. These extensions are motivated by three challenges. One challenge is the lateral wave, which propagates in proximity of the air-earth interface and represents the predominant radiation mechanism for wide-area surveillance, sensing of denied terrain, or close-in sensing. A second challenge is the direct-path coupling between transmitters (Txs) and receivers (Rxs), that affects the measurements. A third challenge is the generation of clutter by the unknown distribution of anomalies embedded in the ground. These challenges are addressed and solved using the following strategies: 1) A forward model for RF tomography that accounts for lateral waves expressed in closed form (for fast computation); 2) a strategy that reduces the direct-path coupling between any Tx-Rx pair; and 3) an improved inversion scheme that is robust with respect to noise, clutter, and high attenuation. A finite-difference time domain simulation of a scenario representing close-in sensing of a denied area is performed, and reconstructed images obtained using the improved and the classical models of RF tomography are compared. View full abstract»

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  • The Impact of Radar Incidence Angle on Soil-Moisture-Retrieval Skill

    Page(s): 501 - 505
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (280 KB) |  | HTML iconHTML  

    The impact of measurement incidence angle (θ) on the accuracy of radar-based surface soil-moisture (Θs) retrievals is largely unknown due to discrepancies in theoretical backscatter models as well as limitations in the availability of sufficiently extensive ground-based Θs observations for validation. Here, we apply a data-assimilation-based evaluation technique for remotely sensed Θs retrievals that does not require ground-based soil-moisture observations to examine the sensitivity of skill in surface Θs retrievals to variations in θ. Past results with the evaluation approach have shown that it is capable of detecting relative variations in the anomaly correlation coefficient between remotely sensed Θs retrievals and ground-truth soil-moisture measurements. Application of the evaluation approach to the Vienna University of Technology (TU Wien) European Remote Sensing (ERS) scatterometer Θs data set over regional-scale ( ~ 10002 km2) domains in the Southern Great Plains and southeastern (SE) regions of the U.S. indicate a relative reduction in correlation-based skill of 23% to 30% for Θs retrievals obtained from far-field (θ>50°) ERS observations relative to Θs estimates obtained at θ <; 26°. Such relatively modest sensitivity to θ is consistent with Θs retrieval noise predictions made using the TU-Wien ERS Water Retrieval Package 5 backscatter model. However, over moderate vegetation cover in the SE domain, the coupling of a bare soil backscatter model with a “vegetation water cloud” canopy model is shown to overestimate the impact of θ on Θs retrieval skill. View full abstract»

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  • Low-Frequency Limit of Unified Models for Backscattering From Oceanlike Surfaces

    Page(s): 506 - 510
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (518 KB) |  | HTML iconHTML  

    In the context of electromagnetic-wave backscattering from oceanlike surfaces, by using the first two orders of unified models, like the small slope approximation and the local curvature approximation, we recently proposed an original technique to reduce the number of numerical integrations to two for easier numerical implementation. In this letter, this technique is simplified in the low-frequency limit, allowing us to bring a correction to the first-order small perturbation method. View full abstract»

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  • Correcting Airborne Laser Scanning Intensity Data for Automatic Gain Control Effect

    Page(s): 511 - 514
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (567 KB) |  | HTML iconHTML  

    The intensity data recorded by airborne laser scanning (ALS) systems are useful for several applications, e.g., automatic point classification, change detection, and environmental studies. Before the intensity values can be used for any specific application, it has to be calibrated for atmospheric effect, range, energy loss, and incidence angle. Some ALS systems use automatic gain control (AGC). AGC is useful for getting laser returns even from low-reflectance surfaces (e.g., dark roofs), but it also changes the recorded intensity during the data acquisition, even within one surface type. This means that the same asphalt road might have totally different intensity values depending on the surrounding environment, which has affected the state of the AGC level. Therefore, it is important to correct the intensity values to neglect the effect of AGC in order to be able to get a normalized intensity value, which is only affected by the target characteristics. A first approach to correct the intensity values for AGC is reported in this letter. The same area was flown with AGC on and off, which allowed the modeling to take place. The results showed that the model produces values that agreed with an R2 of 0.76 to the intensities obtained when AGC was turned off. View full abstract»

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  • Simulation of Low-Resolution Panchromatic Images by Multivariate Linear Regression for Pan-Sharpening IKONOS Imageries

    Page(s): 515 - 519
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1087 KB) |  | HTML iconHTML  

    The extraction of spatial details is crucial for fusion quality. An efficient way is to exploit the difference between high-resolution panchromatic (Pan) images and low-resolution Pan (LRP), which is to be simulated by weighted average value from low-resolution multispectral images. To obtain the weighting coefficients with multivariate linear regression, three issues were discussed, and corresponding solutions were proposed in this letter. The proposed method consists of separating high-frequency pixels from low-frequency pixels using support vector machine and selecting observations that are evenly distributed by a bucketing technique and forcing coefficients to be sound physically by constrained least squares. Validation experiments are undertaken using three IKONOS data sets, and fusion results are compared against four popular methods. The results show that the proposed method can simulate LRP soundly and therefore achieve a better fusion quality. View full abstract»

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  • A Multispectral Image Segmentation Method Using Size-Weighted Fuzzy Clustering and Membership Connectedness

    Page(s): 520 - 524
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (494 KB) |  | HTML iconHTML  

    Clustering-based image segmentation is a well-known multispectral image segmentation method. However, as it inherently does not account for the spatial relation among image pixels, it often results in inhomogeneous segmented regions. The recently proposed membership-connectedness (MC)-based segmentation method considers the local and global spatial relations besides the fuzzy clustering stage to improve segmentation accuracy. However, the inherent spatial and intraclass redundancies in multispectral images might decrease the accuracy and efficiency of the method. This letter addresses these two problems and proposes a segmentation method that is based on the MC method, watershed transform, and the proposed size-weighted fuzzy clustering method. The conducted experiments demonstrate the strength of the proposed algorithm in segmenting small objects, which plays an important role in remote-sensing image segmentation applications. 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