| 1. |
- Gomes, Natanael Rodrigues, et al.
(author)
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Comparison of the Rayleigh and K-Distributions for Application in Incoherent Change Detection
- 2019
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In: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 16, s. 756-760
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Journal article (peer-reviewed)abstract
- The aim of this letter is to compare two incoherent change-detection algorithms for target detection in low-frequency ultrawideband (UWB) synthetic aperture radar (SAR) images. The considered UWB SAR operates in the frequency range from 20 to 90 MHz. Both approaches employ a likelihood ratio test according to the Neyman–Pearson criterion. First, the bivariate Rayleigh probability distribution is used to implement the likelihood ratio test function. This distribution is well known and has been used for change-detection algorithms in low-frequency UWB SAR with good results. Aiming to minimize the false alarm rate and taking into consideration that low-frequency UWB SAR images have high resolution compared to the transmitted wavelength, the second approach implements the test by using a bivariate K-distribution. This distribution has scale and shape parameters that can be used to adjust it to the data. No filter is applied to the data set images, and the results show that with a good statistical model, it is not needed to rely on filtering the data to decrease the number of false alarms. Therefore, we can have a better tradeoff between resolution and detection performance.
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| 2. |
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| 3. |
- Pettersson, Mats, 1966-, et al.
(author)
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Incoherent detection of man-made objects obscured by foliage in forest area
- 2017
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In: International Geoscience and Remote Sensing Symposium (IGARSS). - : Institute of Electrical and Electronics Engineers Inc.. - 9781509049516 ; , s. 1892-1895
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Conference paper (peer-reviewed)abstract
- The paper introduces a new likelihood ratio test (LRT) for incoherent detection of man-made objects obscured by foliage in forest area. The test is performed to detect changes between a reference image and a surveillance image. The method is developed for change detection in high resolution Synthetic Aperture Radar (SAR). For simplicity and lack of more appropriate models, the new LRT is still based on simple and efficient models. If there is no man-made object, the statistical model for clutter and noise of two images will be a bivariate Rayleigh distribution. In contrary, a joint distribution of Rayleigh and uniform is used to model for target, clutter, and noise. The proposed LRT is evaluated using radar data acquired by CARABAS in northern Sweden. The probability of detection is up to 96% with much less than one false alarm per square kilometer. © 2017 IEEE.
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| 4. |
- Vu, Viet Thuy, et al.
(author)
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Bivariate Gamma Distribution for Wavelength-Resolution SAR Change Detection
- 2019
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In: IEEE Transactions on Geoscience and Remote Sensing. - : Institute of Electrical and Electronics Engineers Inc.. - 0196-2892 .- 1558-0644. ; 57:1, s. 473-481
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Journal article (peer-reviewed)abstract
- A gamma probability density function (pdf) is shown to be an alternative to model the distribution of the magnitudes of high-resolution, i.e., wavelength-resolution, synthetic aperture radar (SAR) images. As investigated in this paper, it is more appropriate and more realistic statistical in comparison with, e.g., Rayleigh. A bivariate gamma pdf is considered for developing a statistical hypothesis test for wavelength-resolution incoherent SAR change detection. The practical issues in implementation of statistical hypothesis test, such as assumptions on target magnitudes, estimations for scale and shape parameters, and implementation of modified Bessel function, are addressed. This paper also proposes a simple processing scheme for incoherent change detection to validate the proposed statistical hypothesis test. The proposal was experimented with 24 CARABAS data sets. With an average detection probability of 96%, the false alarm rate is only 0.47 per square kilometer. IEEE
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| 5. |
- Vu, Viet Thuy, et al.
(author)
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Stability in Sar Change Detection Results Using Bivariate Rayleigh Distribution for Statistical Hypothesis Test
- 2019
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In: International Geoscience and Remote Sensing Symposium (IGARSS). - : Institute of Electrical and Electronics Engineers Inc.. - 9781538691540 ; , s. 37-40
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Conference paper (peer-reviewed)abstract
- A statistical hypothesis test for wavelength-resolution SAR change detection can be derived with the bivariate distributions such as Rayleigh, Gamma and K. The paper investigates the stability of change detection results obtained with a statistical hypothesis test using bivariate Rayleigh distribution. Some practical issues concerning the implementation of the statistical hypothesis test such as scale parameter estimation, target magnitude assumptions and Bessel function calculation are also addressed. The statistical hypothesis test using bi-variate Rayleigh distribution are experimented with the data set containing 24 CARABAS II images. It is shown that beside the simplicity and efficiency, a statistical hypothesis test using bivariate Rayleigh distribution can provide very stable change detection results. © 2019 IEEE.
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| 6. |
- Vu, Viet Thuy, et al.
(author)
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Wavelength-resolution SAR Change Detection with Changing Flight Heading during Passes
- 2019
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In: 2019 International Radar Conference, RADAR 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728126609
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Conference paper (peer-reviewed)abstract
- The paper proposes a solution for the problem of target angular observation and specular reflection of elongated structure in SAR change detection. To illuminate a certain target at different angles and/or to minimize specular reflection, a natural solution is to pass the ground scene several times using different flight tracks. This helps to increase the detection probability and reduce the false alarm rate simultaneously. To evaluate the proposal, we use a simple statistical hypothesis test derived from bivariate Rayleigh distribution and the CARABAS data. A comparison based on the detection probability and false alarm rate with other available SAR change detection method reveals the benefit of the proposal. © 2019 IEEE.
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