Jong-Sen Lee

SpecTIR™ Remote Sensing Division, Reno, Nevada, United States

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Publications (85)107.33 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: At high resolution, synthetic aperture radar (SAR) speckle tends to be non-Gaussian distributed and diversely textured. Many parametric speckle distributions have been developed to fit specific in-scene content. In contrast, mixture models offer an empirical approximation with the potential to fit arbitrary variations. In this letter, we investigate the feasibility and the efficiency of using finite mixture models of an identical parametric kernel to characterize the wide range of high-resolution speckle. We evaluate and compare the capability of mixture fitting with gamma, $mathcal{K}$, and $mathcal{G}^{0}$ kernels against various scene types. Despite the characterization disparity among these base kernels, we show that using any of them in a mixture setting rapidly improves speckle modeling. Finite gamma mixtures, even with a simple kernel form, are applicable to high-resolution SAR imagery for consistent description of complex textured speckle variations.
    IEEE Geoscience and Remote Sensing Letters 05/2015; 12(5):968-972. DOI:10.1109/LGRS.2014.2370095 · 1.81 Impact Factor
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    ABSTRACT: The advancement of synthetic aperture radar (SAR) technology with high-resolution and quad-polarization data demands better and efficient polarimetric SAR (PolSAR) speckle-filtering algorithms. Two requirements on PolSAR speckle filtering are proposed: 1) speckle filtering should be applied to distributed media only, and strong hard targets should be kept unfiltered; and 2) scattering mechanism preservation should be taken into consideration, in addition to speckle reduction. The purpose of this paper is twofold: 1) to propose an effective algorithm that is an extension of the improved sigma filter developed for single-polarization SAR; and 2) to investigate speckle characteristics and the need for speckle filtering for very high resolution (decimeter) PolSAR data. The proposed filter was specifically developed to account for the aforementioned two requirements. Its effectiveness is demonstrated with Jet Propulsion Laboratory airborne synthetic aperture radar data, and comparisons are made with a boxcar filter, the refined Lee filter, and a Wishart-based nonlocal filter. For very high resolution PolSAR systems, such as the German Aerospace Center F-SAR and Japanese Pi-SAR2, with decimeter spatial resolution, we found that the complex Wishart distribution is still valid to describe PolSAR speckle characteristics of distributed media and that speckle filtering may be needed depending on the size of objects to be analyzed. F-SAR X-band data with 25-cm resolution is used for illustration.
    IEEE Transactions on Geoscience and Remote Sensing 03/2015; 53(3):1150-1160. DOI:10.1109/TGRS.2014.2335114 · 2.93 Impact Factor
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    ABSTRACT: The model-based scattering decomposition pioneered by Freeman and Durden has stimulated research in characterizing polarimetric synthetic aperture radar (PolSAR) scattering phenomenon and its applications. The Freeman and Durden decomposition as originally developed is based on three scattering models for volume, surface, and double bounce. It is known that the decomposition often produces negative scattering powers for a large number of pixels. This implies that the scattering models are inconsistent with the data. In this paper, we investigate the model deficiency problem and propose several algorithms to mitigate it. To achieve this, we developed an incoherent scattering model based on the polarization orientation angle distribution of phase differences. Two approaches are taken to reduce the number of negative power pixels: 1) adopt a volume scattering model by including variable shape factor while keeping the original surface and double bounce models unchanged, and 2) incorporate the incoherent surface or double bounce model while keeping the original volume model. In addition, the combination of 1) and 2) is explored, and the effect of polarization orientation compensation on these algorithms is investigated. The effectiveness of these approaches is compared using L-band AIRSAR and E-SAR PolSAR data. It will be shown that model efficiency is improved with occurrence of negative power reduced to an insignificant level.
    IEEE Transactions on Geoscience and Remote Sensing 04/2014; 52(5). DOI:10.1109/TGRS.2013.2262051 · 2.93 Impact Factor
  • Chin-Fu Chao, Kun-Shan Chen, Jong-Sen Lee
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    ABSTRACT: Radar interferometry has been widely applied in measuring the terrain height and its changes. The information about surface can be derived from phase interferograms. However, the inherent phase noise reduces the accuracy and reliability of that information. Hence, the minimization of phase noise is essential prior to the retrieval of surface information that is embedded in an interferometric phase. This paper presents a refined filter based on the Lee adaptive complex filter and the improved sigma filter that was originally developed for amplitude image filtering. The basic idea is to adaptively filter the interferometric phase according to the local noise level to minimize the loss of signal for a particular pattern of fringes, including such extreme cases as involving broken fringes, following the removal of undesired pixels. Ultimately, the goals are to preserve the fringe pattern, to reduce phase bias and deviation, to reduce the number of residues, and to minimize the phase error. The preservation of the fringe pattern is particularly of concern in areas of high frequency of fringe and large phase gradient corresponding to steep terrains. The proposed refined filter was validated using both simulated data and real interferometric data. Results demonstrate that the filtering performance is better than that of commonly used filters.
    IEEE Transactions on Geoscience and Remote Sensing 12/2013; 51(12):5315-5323. DOI:10.1109/TGRS.2012.2234467 · 2.93 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recent studies have shown that the volumetric scatterers of different canopy types warranted varying scattering models, which feature different orientation and shape characteristics. In this paper, we explore the possibility of estimating the orientation and shape parameters from POLSAR observations. Both the orientation and shape parameters of the canopy are defined by a cloud of spheroids with independent orientation and shape distributions. The respective parameters clearly express themselves in the circular polarization basis in which we derive the analytic solutions. Applying the estimation to POLSAR data, we demonstrate these parameters capable of characterizing the canopy scatterers, providing a consistent physical interpretation of the target scattering mechanisms and generating a fine-grained initialization for Wishart classifications of vegetation and forest targets.
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 06/2012; 5(3):835-847. DOI:10.1109/JSTARS.2012.2192718 · 2.83 Impact Factor
  • Jong-Sen Lee, T.L. Ainsworth, Yanting Wang
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    ABSTRACT: The Freeman and Durden decomposition as original developed is based on three scattering models for volume, surface and double bounce. It is known that the decomposition produces negative scattering powers for a large number of pixels. This implies that the scattering models are inconsistent with the data. In this paper, we investigate the negative power problem and propose two algorithms to mitigate it. To achieve this, alternative scattering models have been adopted, and new families of incoherent scattering models are developed. The effectiveness of these approaches is compared using L-band E-SAR polarimetric data. It will be shown that the negative power problem can be reduced to an insignificant level.
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 01/2012
  • Yanting Wang, T.L. Ainsworth, Jong-Sen Lee
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    ABSTRACT: A feature space for scatterer characterization is constructed of the geophysical parameters of scatterers on size, shape, and orientation. Dense divisions are defined to discriminate target classes of possibly subtle distinction. The statistical similarity and uncertainty of overlapping cluster pairs are evaluated with Wishart based likelihood ratio and at a desired level of false classification the dense set of clusters is hierarchically pruned. Wishart based classification is then applied to the whole imagery, accomplishing a physical-based unsupervised classification algorithm. The algorithm is illustrated using an AIRSAR dataset of San Francisco to evaluate its capability in characterizing complex terrains. As an optional step, the K-Means or Expectation-Maximization iteration is performed to further adapt the cluster centers.
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 01/2012
  • Jong-Sen Lee, T.L. Ainsworth, Yanting Wang
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    ABSTRACT: The advancement of SAR technology with high resolution and quad-polarization data demands better and efficient speckle filtering algorithms. In principle, filtering should be applied to distributed media only. Strong pointed targets should be kept unfiltered. In this paper, we will review some of the recently published PolSAR speckle filtering algorithms, and discuss several important issues that affect the speckle filtering results.
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International; 01/2012
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    ABSTRACT: Terrain and land use classification is one of the most important applications of polarimetric synthetic aperture radar [1]. Various methods have been proposed to classify terrain based on polarimetric statistical characteristics. A four-component scattering decomposition [2] scheme based on the coherency matrix [3] has been proposed to supplement the common three-component decomposition by Freeman and Durden[4] by adding a helix components that represent scattering contribution from complex urban environment. This paper applies the four-component decomposition to analyze the polarimetric response of rice crop from time series of polarimetric SAR data acquired from RADARSAT-2. To trace the growth stage, change detection was performed over the four components, with surface scattering, volume scattering, double bounce, and helix scattering as feature vector, using CFAR detector.
    Antennas and Propagation (ISAP), 2012 International Symposium on; 01/2012
  • Yanting Wang, T.L. Ainsworth, Jong-Sen Lee
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    ABSTRACT: The quality of polarimetric synthetic aperture radar (PolSAR) imagery and its polarimetric decompositions depends on the accuracy of polarimetric observations of the SAR system and its calibration. Polarization distortions on the polarimetric measurement can be incurred due to nonideal system polarization quality and propagation factors, such as channel imbalance, crosstalk, and Faraday rotation at lower frequencies. All these distortions have varying impacts on different target types as well as different decomposition methods. In this paper, we assess the polarization quality of the PolSAR system in the context of polarimetric imagery analysis and quantify the various effects of polarization distortions on polarization target decompositions. A generic metric is defined to measure the polarization purity of the system. Considering the fact that target decomposition plays an important role in imagery analysis, we apply several widely used decomposition methods to showcase the polarimetric system requirement based on the defined metric. We demonstrate that this metric can be used for radar system design and polarimetric data calibration.
    IEEE Transactions on Geoscience and Remote Sensing 06/2011; DOI:10.1109/TGRS.2010.2087342 · 2.93 Impact Factor
  • Jong-Sen Lee, T.L. Ainsworth
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    ABSTRACT: The polarization orientation angle (OA) of the scattering media affects the polarimetric radar signatures. This paper investigates the effects of orientation compensation on the coherency matrix and the scattering-model-based decompositions by Freeman-Durden and Yamaguchi et al. The Cloude and Pottier decomposition is excluded, because entropy, anisotropy, and alpha angle are roll invariant. We will show that, after orientation compensation, the volume scattering power is consistently decreased, while the double-bounce power has increased. The surface scattering power is relatively unchanged, and the helicity power is roll invariant. All of these characteristics can be explained by the compensation effect on the nine elements of the coherency matrix. In particular, after compensation, the real part of the (HH - VV) · HV* correlation reduces to zero, the intensity of cross-pol |HV| always reduces, and |HH - VV| always increases. This analysis also reveals that the common perception that OA compensation would make a reflection asymmetrical medium completely reflection symmetric is incorrect and that, contrary to the general perception, the four-component decomposition does not use the complete information of the coherency matrix. Only six quantities are included - one more than the Freeman-Durden decomposition, which explicitly assumes reflection symmetry.
    IEEE Transactions on Geoscience and Remote Sensing 02/2011; DOI:10.1109/TGRS.2010.2048333 · 2.93 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we set to investigate the orientation and structure parameters retrieved from POLSAR observations for canopy scattering and evaluate their capability to improving physical retrievals for vegetation and forest targets. Both the orientation and structure parameters of the canopy can be described as a cloud of spheroids with independent orientation distribution and shape distribution. The respective parameters express themselves in a clearer form in the circular polarization basis. The findings on the orientation and structure parameters are used to assist Wishart based polarimetric classification.
    2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011, Vancouver, BC, Canada, July 24-29, 2011; 01/2011
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    ABSTRACT: In this paper, we propose a terrain categorization algorithm for single-polarization high-resolution SAR imagery, and coded the terrain categories by colors that resemble Pauli decomposition color coding based on scattering mechanisms of PolSAR data. The proposed algorithm emphasizes preserving high resolution and making information dissemination easier for single-pol SAR data. The success of TerraSAR-X and RadarSAT-2 has provided Earth remote sensing with high-resolution SAR data in single, dual and quad polarizations. It is well known that the single polarization mode has the advantages in the large swath for wide area coverage, and in data handling, but single-pol SAR has the deficiency in separating scattering mechanisms compared with dual and quad-pol SAR. Consequently, terrain categorization based on single-pol data is a difficult task. The recent advances in polarimetric SAR technology in understanding scattering behavior make it feasible to investigate the possibility of classifying terrains by scattering mechanisms based on single-pol reflectivity alone. In this paper, we will attempt to classify the single-pol image into surface scattering, volume scattering, and double bounce scattering. The image is then color coded in a way that resembles Pauli color-coding from polarimetric SAR data. To further separate inland water surface from rougher ground surface, a color rendering scheme is developed, and a procedure to color rough ocean surface is also established. High-resolution SAR data demands computational efficient algorithms, because even single-pol high-resolution data, such as TerraSAR-X, has very large dimensions, typically some twenty-thousand by twenty-thousand pixels. Moreover, maintaining spatial resolution is desirable. The final result is encouraging, but we emphasize that single-pol SAR can not replace fully polarimetric SAR, because the latter has much higher discriminating capability when
    IEEE International Geoscience and Remote Sensing Symposium (IGARSS); 01/2011
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    ABSTRACT: In the last decade, the three-component polarimetric scattering decomposition by Freeman and Durden has stimulated research and applications in model-based decompositions. In this paper, we will review recent advances in the scattering models, focusing on the negative power problem and its mitigation, the problem of the reflection symmetry assumption, and the effect of orientation angle compensation. An extended decomposition based on the extended Bragg model is also proposed. Polarimetric SAR images illustrate our approach.
    2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011, Vancouver, BC, Canada, July 24-29, 2011; 01/2011
  • Jong-Sen Lee, T.L. Ainsworth
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    ABSTRACT: Recent advances in Polarimetric SAR information extractions are reviewed. Papers published in IEEE Transactions on Geoscience and Remote Sensing and IGARSS proceedings over the last five years were included. We found that PolSAR technology has reached a certain degree of maturity. The availability of high-resolution multi-frequency PolSAR data from space borne and airborne SAR systems will stimulate significant PolSAR applications.
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International; 08/2010
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    ABSTRACT: This paper addresses the feasibility of using RADARSAT-2 fine Quad-Pol mode to monitor coastal environment and young tree growth. It will be shown that interferometric coherence may not be high enough for the height estimation of young trees at C-band, but polarimetric sensitivity could be used for tree and crop classification. For coastal environment, we found that polarimetric signature of oyster farm reveals the effect of double bounce scattering and the orientation angle effects.
    IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2010, July 25-30, 2010, Honolulu, Hawaii, USA, Proceedings; 01/2010
  • [Show abstract] [Hide abstract]
    ABSTRACT: The quality of polarimetric synthetic aperture radar (PolSAR) imagery and its polarimetric decompositions depends on the accuracy of polarimetric observations of the SAR system and its calibration. Polarization distortions on the polarimetric measurement can be incurred due to nonideal system polarization quality and propagation factors, such as channel imbalance, cross-talk, and Faraday rotation at lower frequencies. All these distortions have varying impacts on different target types as well as different decomposition methods. In this paper, we assess the polarization quality of the PolSAR system in the context of polarimetric imagery analysis and quantify the various effects of polarization distortions on polarization target decompositions. A generic metric is defined to measure the polarization purity of the system. Considering the fact that target decomposition plays an important role in imagery analysis, we apply several widely used decomposition methods to showcase the polarimetric system requirement based on the defined metric.
    IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2010, July 25-30, 2010, Honolulu, Hawaii, USA, Proceedings; 01/2010
  • Jong-Sen Lee, T.L. Ainsworth, Kun-Shan Chen
    [Show abstract] [Hide abstract]
    ABSTRACT: The orientation angle of scattering media affects the polarimetric radar signatures. This paper investigates the effect of orientation compensation on polarimetric target decompositions including Pauli decomposition, Freeman and Durden decomposition and Yamaguchi decomposition. The Cloude and Pottier decomposition is excluded, because entropy, anisotropy and alpha angle are rotational invariant. We will show that after the orientation compensation, the volume scattering power is consistently decreased, while the double bounce power has increased. The surface scattering power is relatively unchanged, and the helicity power is rotational invariant. All these characteristics can be explained by the compensation effect on the nine elements of the coherency matrix. This analysis reveals that, contrary to the general perception, the 4-component component decomposition by Yamaguichi et al. does not use complete information of the coherency matrix. Only six quantities are included - one more than the Freeman/Durden decomposition under the assumption of refection symmetry.
    Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009; 08/2009
  • Jong-Sen Lee, Eric Pottier
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    ABSTRACT: The recent launches of three fully polarimetric synthetic aperture radar (PolSAR) satellites have shown that polarimetric radar imaging can provide abundant data on the Earth’s environment, such as biomass and forest height estimation, snow cover mapping, glacier monitoring, and damage assessment. Written by two of the most recognized leaders in this field, Polarimetric Radar Imaging: From Basics to Applications presents polarimetric radar imaging and processing techniques and shows how to develop remote sensing applications using PolSAR imaging radar. The book provides a substantial and balanced introduction to the basic theory and advanced concepts of polarimetric scattering mechanisms, speckle statistics and speckle filtering, polarimetric information analysis and extraction techniques, and applications typical to radar polarimetric remote sensing. It explains the importance of wave polarization theory and the speckle phenomenon in the information retrieval problem of microwave imaging and inverse scattering. The authors demonstrate how to devise intelligent information extraction algorithms for remote sensing applications. They also describe more advanced polarimetric analysis techniques for polarimetric target decompositions, polarization orientation effects, polarimetric scattering modeling, speckle filtering, terrain and forest classification, manmade target analysis, and PolSAR interferometry. With sample PolSAR data sets and software available for download, this self-contained, hands-on book encourages you to analyze space-borne and airborne PolSAR and polarimetric interferometric SAR (Pol-InSAR) data and then develop applications using this data.
    02/2009; CRC Press., ISBN: 9781420054989
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    ABSTRACT: The Lee sigma filter was developed in 1983 based on the simple concept of two-sigma probability, and it was reasonably effective in speckle filtering. However, deficiencies were discovered in producing biased estimation and in blurring and depressing strong reflected targets. The advancement of synthetic aperture radar (SAR) technology with high-resolution data of large dimensions demands better and efficient speckle filtering algorithms. In this paper, we extend and improve the Lee sigma filter by eliminating these deficiencies. The bias problem is solved by redefining the sigma range based on the speckle probability density functions. To mitigate the problems of blurring and depressing strong reflective scatterers, a target signature preservation technique is developed. In addition, we incorporate the minimum-mean-square-error estimator for adaptive speckle reduction. Simulated SAR data are used to quantitatively evaluate the characteristics of this improved sigma filter and to validate its effectiveness. The proposed algorithm is applied to spaceborne and airborne SAR data to demonstrate its overall speckle filtering characteristics as compared with other algorithms. This improved sigma filter remains simple in concept and is computationally efficient but without the deficiencies of the original Lee sigma filter.
    IEEE Transactions on Geoscience and Remote Sensing 02/2009; 47(1-47):202 - 213. DOI:10.1109/TGRS.2008.2002881 · 2.93 Impact Factor

Publication Stats

3k Citations
107.33 Total Impact Points

Institutions

  • 2008
    • SpecTIR™ Remote Sensing Division
      Reno, Nevada, United States
  • 2007–2008
    • National Central University
      • Center for Space and Remote Sensing Research
      Taoyuan City, Taiwan, Taiwan
    • Institute for Environmental Protection and Research (ISPRA)
      Roma, Latium, Italy
  • 2003
    • National Research Council
      Roma, Latium, Italy
    • Hsing Wu University
      T’ai-pei, Taipei, Taiwan
  • 2001
    • Université de Rennes 1
      Roazhon, Brittany, France
    • University of Massachusetts Dartmouth
      • Department of Electrical and Computer Engineering
      New Bedford, Massachusetts, United States