Novel Polarimetric Contrast Enhancement Method Based on Minimal Clutter to Signal Ratio Subspace

Yang, Dongwen; Du, Lan; Liu, Hongwei; Ni, Wei

doi:10.1109/tgrs.2019.2921629

Cited by 8 publications

(6 citation statements)

References 19 publications

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“…It should be noted that the NPCM is not necessary. It can also be made by the coefficients of different polarimetric decompositions [14], or the 3-dimensional polarimetric covariance matrix, as shown in the measured dataset. We can also find that the high dimension may improve the detection performance.…”

Section: A Simulated Data Generationmentioning

confidence: 99%

“…Here, five methods to solve the trace ratio problem are compared using the Monte Carlo method: MCSR-Y [14], IITR [22], ITR-score [24], and IITR-score. The absolute bias  and computation time (s) are listed in Table II.…”

Section: B Efficiency Of the Tr Problem Solutionmentioning

confidence: 99%

“…A generalized OPCE (GOPCE) was proposed to include different scattering mechanisms between targets and clutter [13]. Recently, a novel polarimetric contrast enhancement method based on the minimal clutter-to-signal ratio (MCSR) subspace was proven to be more flexible [14], where OPCE and GOPCE can be seen as special cases of MCSR. However, the optimal dimension of the MSCR subspace has yet to be resolved, and the solution for the optimization is only numerical.…”

Section: Introductionmentioning

confidence: 99%

“…As noted by Novak et al, detection performance is not only dependent on TCR, but also depends on clutter fluctuation [19]. Combining the objectives of PMF and PWF, and inspired by the subspace theory of MCSR [14], Tao et al proposed a polarimetric detection optimization filter (PDOF) and its approximate subspace form (APDOF), which can provide performance similar to those of the best traditional detectors [6]. However, the derivation of APDOF maximizes the numerator TCR and minimizes the denominator fluctuation independently [6], rather than maximizing the overall value of their ratios simultaneously, which is not a strict solution in mathematics.…”

Section: Introductionmentioning

confidence: 99%

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Joint Polarimetric Subspace Detector Based on Modified Linear Discriminant Analysis

Liu

Yang

Marino

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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Polarimetric synthetic aperture radar (PolSAR) is widely used in remote sensing and has important applications in the detection of ships. Although many polarimetric detectors have been proposed, they are not well combined. Recently, a polarimetric detection optimization filter (PDOF) was proposed that performs well in most environments. In this study, a novel subspace form of the PDOF (SPDOF) was further developed based on the Cauchy inequality and matrix decomposition theories, enhancing detection performance. Furthermore, a simple method to determine the optimal dimension of the subspace detector based on the trace ratio form was proposed by calculating the area under the receiver operating characteristic (ROC) curve, reaching the best detection performance among the subspaces of the detector. Moreover, to combine different subspace detectors, a modified linear discriminant analysis was proposed and developed to the diagonal loading detector (DLD) based on polarimetric subspaces. The experimental results demonstrate the superiority of these joint polarimetric subspace detectors. Most importantly, DLD solves for previous limitations due to the complex clutter background and achieves a performance comparable to that of the Wishart (Gaussian) distribution, particularly in the low target clutter ratio (TCR) case.

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Section: A Simulated Data Generationmentioning

confidence: 99%

Section: B Efficiency Of the Tr Problem Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Joint Polarimetric Subspace Detector Based on Modified Linear Discriminant Analysis

Liu

Yang

Marino

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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“…Liu et al proposed a new optimal technique by combining the PMF and PNF to maximize the TCR and minimize the speckle noise, which was referred to as the polarimetric detection optimization filter (PDOF) [13]. Yang et al proposed a novel optimal polarimetric enhancement method based on the minimal clutter-to-signal (MCSR) subspace [14]. Chen et al developed the uniform polarimetric matrix transformation theory [15] and proposed a visualization and characterization tool for PolSAR data investigation called polarimetric correlation pattern [16].…”

Section: Introductionmentioning

confidence: 99%

PolSAR Ship Detection Based on a SIFT-like PolSAR Keypoint Detector

Gu¹,

Wang²,

Liu³

et al. 2022

Remote Sensing

Self Cite

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The detection of ships on the open sea is an important issue for both military and civilian fields. As an active microwave imaging sensor, synthetic aperture radar (SAR) is a useful device in marine supervision. To extract small and weak ships precisely in the marine areas, polarimetric synthetic aperture radar (PolSAR) data have been used more and more widely. We propose a new PolSAR ship detection method which is based on a keypoint detector, referred to as a PolSAR-SIFT keypoint detector, and a patch variation indicator in this paper. The PolSAR-SIFT keypoint detector proposed in this paper is inspired by the SAR-SIFT keypoint detector. We improve the gradient definition in the SAR-SIFT keypoint detector to adapt to the properties of PolSAR data by defining a new gradient based on the distance measurement of polarimetric covariance matrices. We present the application of PolSAR-SIFT keypoint detector to the detection of ship targets in PolSAR data by combining the PolSAR-SIFT keypoint detector with the patch variation indicator we proposed before. The keypoints extracted by the PolSAR-SIFT keypoint detector are usually located in regions with corner structures, which are likely to be ship regions. Then, the patch variation indicator is used to characterize the context information of the extracted keypoints, and the keypoints located on the sea area are filtered out by setting a constant false alarm rate threshold for the patch variation indicator. Finally, a patch centered on each filtered keypoint is selected. Then, the detection statistics in the patch are calculated. The detection statistics are binarized according to the local threshold set by the detection statistic value of the keypoint to complete the ship detection. Experiments on three data sets obtained from the RADARSAT-2 and AIRSAR quad-polarization data demonstrate that the proposed detector is effective for ship detection.

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SAR Image Enhancement Based on P-M Nolinear Diffusion and Coherent Enhancement Diffusion

Chen

et al. 2020

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium

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Novel Polarimetric Contrast Enhancement Method Based on Minimal Clutter to Signal Ratio Subspace

Cited by 8 publications

References 19 publications

Joint Polarimetric Subspace Detector Based on Modified Linear Discriminant Analysis

Joint Polarimetric Subspace Detector Based on Modified Linear Discriminant Analysis

PolSAR Ship Detection Based on a SIFT-like PolSAR Keypoint Detector

SAR Image Enhancement Based on P-M Nolinear Diffusion and Coherent Enhancement Diffusion

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