Detection of linear features using a localized Radon transform

Warrick, A.; Delaney, P.A.

doi:10.1109/acssc.1996.599144

Cited by 13 publications

(9 citation statements)

References 6 publications

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“…After the QRCM is corrected, it is necessary to measure a small and discrete number of slopes exhibited in the (t, h 1 ) domain. The RRT is an effective way to measure the slope of a straight line [18,23]. Since the RRT only uses the amplitude information, its result can be impacted by the low SNR.…”

Section: Ambiguity Estimation Using the Mfrrtmentioning

confidence: 99%

Improved ambiguity estimation using a modified fractional Radon transform

Sun

Xing

Wang

et al. 2011

IET Radar Sonar Navig.

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Ambiguity estimation is critical for the positioning of a moving target truly. Traditional real-value Radon transform (RRT) has been used to estimate the slope of target's trajectory such that the ambiguity number can be derived. However, the unknown azimuth velocity of the target makes it difficult to determine the ambiguity number because the quadratic range cell migration (QRCM) caused by the platform velocity reduces the sensitivity of the RRT in the estimation. Also, the RRT does not work well when the signal-to-noise ratio (SNR) is low. Here, a method that uses the second-order Keystone transform (SOKT) to eliminate the QRCM and the modified fractional Radon transform (MFrRT) to estimate the ambiguity number was proposed. The method was simple and applicable in the low-SNR situation. Implementation considerations were presented. Finally, the effectiveness of the method has been shown using simulated and acquired synthetic aperture radar datasets.

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Section: Ambiguity Estimation Using the Mfrrtmentioning

confidence: 99%

Improved ambiguity estimation using a modified fractional Radon transform

Sun

Xing

Wang

et al. 2011

IET Radar Sonar Navig.

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“…The Radon transform is an effective technique in extracting the parameters of linear features, such as their slope, even in the presence of noise [6]. Because of its advantageous property in detecting lines with arbitrary orientation, the Radon transform has been successfully used in SAR image processing, such as ship wake detection [8].…”

Section: Radon Transform For Linear Feature Detectionmentioning

confidence: 99%

“…This is referred to as the localized Radon transform in [6]. If the correct ambiguity can be found from only a small part of a scene, the result can be applied to the whole scene, as long as the baseband centroid is unwrapped correctly.…”

Section: ) Integer Estimation Problemmentioning

confidence: 99%

“…The concept is that a concentrated point in the transform space represents a linear feature in the image. This approach is particularly suited for noisy images, since the integration process tends to average out intensity fluctuations due to , is defined as [6] ( 3) where is the Dirac delta function and the factor, , directs the integration along the angle, . The range of the integration angle is limited to .…”

Section: Radon Transform For Linear Feature Detectionmentioning

confidence: 99%

“…In this method, the Doppler ambiguity is estimated by measuring the range displacement of targets between two azimuth looks or, equivalently, by measuring the slope of targets in the range-compressed image. The Radon transform is a well-known method of detecting linear features in an image [6], such as the slope of lines (Sections I-A and II). Kong et al have applied the Radon transform to estimate the Doppler centroid frequency of airborne SAR data in 2005 [7].…”

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Improved slope estimation for SAR Doppler ambiguity resolution

Cumming

2006

IEEE Trans. Geosci. Remote Sensing

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Abstract-The idea of using the Radon transform to measure the alignment of linear features in synthetic aperture radar (SAR) data has breathed new life into the "look displacement" class of Doppler ambiguity resolution algorithms. In these algorithms, the slope of target energy is estimated to obtain the satellite beam pointing angle accurately enough to resolve the Doppler ambiguity. After explaining the method and adding some minor improvements, it is shown how it can work well on satellite SAR data. Then, an alternate method is developed that combines the ideas of the Radon and look displacement algorithms to obtain a computationally simpler and more accurate algorithm. In addition, the quality checks of the "spatial diversity" approach are used to increase the robustness of the algorithm. Even though the algorithm was conceived for high-contrast scenes, it works remarkably well in low to medium contrast scenes as well.Index Terms-Doppler ambiguity resolution, Doppler centroid estimation, Radon transform, synthetic aperture radar (SAR) antenna pointing angle.

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Adaptive Discrete Radon Transforms for Greyscale Images

Kingston

Svalbe

2003

Electronic Notes in Discrete Mathematics

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Detection of linear features using a localized Radon transform

Cited by 13 publications

References 6 publications

Improved ambiguity estimation using a modified fractional Radon transform

Improved ambiguity estimation using a modified fractional Radon transform

Improved slope estimation for SAR Doppler ambiguity resolution

Adaptive Discrete Radon Transforms for Greyscale Images

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