Extended Geometrical Perturbation Based Detectors for PolSAR Image Target Detection in Heterogeneously Patched Regions

Yang, Dongwen; Du, Lan; Liu, Hongwei; Wang, Peng; Gu, Mingfei

doi:10.1109/jstars.2018.2879906

Cited by 10 publications

(14 citation statements)

References 26 publications

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“…Power line extraction: Methods related to power line extraction can be categorized into two types [7,18]: line-shape-based extraction methods (e.g., RANSAC (random sample consensus) and the Hough transformation), and supervised classification methods (e.g., support vector machine (SVM), random forest (RF), JointBoost, and the Markov random field). For instance, McLaughlin [19] used a Gaussian mixture model, together with neighborhood structures, computed by a covariance matrix, to classify airborne LiDAR data of power transmission corridors into three categories: power lines, vegetation, and surfaces.…”

Section: Related Workmentioning

confidence: 99%

“…Exposed to the natural environment in the long term, power lines are often infringed upon by many factors such as lightning, storms, strong wind, bird damage, and vegetation encroachment [1,4], which may result in large-scale blackouts, and even significant financial losses [5,6]. To guarantee the normal transmission of electricity, the regular monitoring and maintenance of power lines are needed [1,7].…”

Section: Introductionmentioning

confidence: 99%

“…For administrative departments that are responsible for power transmission lines, there are basically two main components in transmission line inspection [1,7,8]: power line monitoring (including their structure and components), and surrounding objects monitoring (especially vegetation). For decades, limited by detecting technology, the major methods for traditional transmission line 2 of 23 inspection are field surveys and airborne surveys [1].…”

Section: Introductionmentioning

confidence: 99%

“…For decades, limited by detecting technology, the major methods for traditional transmission line 2 of 23 inspection are field surveys and airborne surveys [1]. Although field-based methods have a high hazard detection rate, both of the above methods are human-dominated, depending on the personal inspection ability, and they have a high level of time consumption and labor intensity [1,7]. Moreover, most of the high-voltage power lines extend to complex environments (e.g., lakes, mountains, and forests), and their distribution is becoming more complicated (e.g., multi-loop and multi-bundle) [9], which are great challenges for the inspection of power lines.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, most of the high-voltage power lines extend to complex environments (e.g., lakes, mountains, and forests), and their distribution is becoming more complicated (e.g., multi-loop and multi-bundle) [9], which are great challenges for the inspection of power lines. With the continuous improvement of hardware and innovative data processing algorithms, various advanced remote sensing data (such as video [1], optical image [10,11], SAR (synthetic aperture radars) [12], thermal image [13], and LiDAR (Light Detection and Ranging) [1,[7][8][9]) and multitudinous monitoring platforms at different ranges (such as satellite, airborne, unmanned aerial vehicles (UAVs) [14,15], mobile mapping [16,17], and cable inspection robot (CIR) [4,9]) have been introduced into the management of smart grids. Compared with other remotely sensed data, airborne LiDAR technology, which can easily acquire high accuracy and high density 3D point clouds over a large range, has been widely applied to the inspection of transmission lines in recent years.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Method for High-Voltage Bundle Conductor Reconstruction from Airborne LiDAR Data

Zhou

Jiang

2018

Remote Sensing

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The security of high-voltage power transmission corridors is significantly vital to the national economy and daily life. With its rapid development, LiDAR (Light Detection and Ranging) technology has been widely applied in the inspection of transmission lines. As the basis of potential hazard detection, a robust and precise power line model is a necessary requirement for rapid and correct clearance. Thus, this paper proposes a novel method for high-voltage bundle conductor reconstruction, which can precisely reconstruct each sub-conductor. First, points in high-voltage power transmission corridors are detected and classified into four categories; second, for classified power lines, single power line spans are extracted, and bundle conductors are identified by analyzing the single spans’ fitting residuals; and then, each sub-conductor of bundle conductors is extracted by a projected dichotomy method on the XOY and XOZ planes, respectively; finally, a double-RANSAC (random sample consensus)-based algorithm was introduced to reconstruct each power line. The proposed method makes use of the distribution of bundle conductors in high-voltage transmission lines, and our experiments showed that it could preferably reconstruct the real structure of bundle conductors robustly with a high precision better than 0.2 m.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Novel Method for High-Voltage Bundle Conductor Reconstruction from Airborne LiDAR Data

Zhou

Jiang

2018

Remote Sensing

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A Novel Hybrid Edge Detection Method for Polarimetric SAR Images

2020

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The edge detection plays an important role in post-processing of PolSAR images. It is still a great challenge for extracting all the edge features and suppress speckle noises, especially when weak/strong edges appear simultaneously outside and within heterogenous areas. In this paper, a novel hybrid edge detection framework is proposed to address this problem. The proposed method is designed by fusing two initial edge detectors, which can detect complementary edge information. One is an improved polarimetric constant false alarm rate (IP_CFAR) edge detector, which can detect weak edges well, but fail to detect the edges in the heterogeneous regions. The other is the proposed weighted gradient-based (WG) detector which can detect edges in heterogeneous areas well, but loses some weak edges and produces some false edges due to the speckle noises. Secondly, based on the two detectors above, a wavelet-based hybrid edge detection method is proposed by combining their merits and suppress their shortcomings. To fuse them effectively, wavelet transformation is utilized and semantic rules are defined to extract their advantages. Moreover, a despeckling scheme is designed to suppress the false edges in the wavelet domain. Experimental results demonstrate that the proposed method outperforms the state-of-art methods in extracting both weak edges and strong edges within heterogeneous regions. INDEX TERMS Hybrid edge detection method, improved polarimetric CFAR detector, weighted gradientbased detector, wavelet fusion.

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Bi-Phase Compound-Gaussian Mixture Model of Sea Clutter and Scene-Segmentation-Based Target Detection

Liang

Shui

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In high-resolution maritime surveillance radars, sea clutter exhibits highly spatial heterogeneity due to modulation of long waves with wavelengths longer than the width of one range cell. Compound-Gaussian model (CGM) fails to characterize the heterogeneous high-resolution sea clutter in both amplitude distribution and Doppler spectrum. In this paper, a bi-phase compound-Gaussian mixture model (BP-CGMM) is proposed to characterize the heterogeneous sea clutter. In the BP-CGMM, spatial resolution cells are grouped into two disjoint sets, and the sea clutter in each set is represented by one CGM with inverse Gamma-distributed texture. The spectral heterogeneity indicates that sea clutter vectors at spatially adjacent resolution cells in one set share the same speckle covariance matrix, while that at two adjacent spatial cells separated in the two sets often have different speckle covariance matrices. The BP-CGMM is validated by a mass of measured high-resolution sea clutter data. Moreover, under the BP-CGMM, a detection method based on batch test is given to detect sea-surface small targets, which is composed of scene segmentation, by the aid of Bayesian threshold and morphological filtering, and adaptive generalized likelihood ratio test linear-threshold detector (GLRT-LTD) separately in each set. The detection method is verified by measured data with small targets under test. The experimental results show that it attains better detection performance than the adaptive GLRT-LTD under the CGM of sea clutter. Index Terms-Modulation of long waves; Heterogeneous high-resolution sea clutter; Compound-Gaussian mixture model; Spectral heterogeneity; Scene segmentation.

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Extended Geometrical Perturbation Based Detectors for PolSAR Image Target Detection in Heterogeneously Patched Regions

Cited by 10 publications

References 26 publications

A Novel Method for High-Voltage Bundle Conductor Reconstruction from Airborne LiDAR Data

A Novel Method for High-Voltage Bundle Conductor Reconstruction from Airborne LiDAR Data

A Novel Hybrid Edge Detection Method for Polarimetric SAR Images

Bi-Phase Compound-Gaussian Mixture Model of Sea Clutter and Scene-Segmentation-Based Target Detection

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