Methods for Blind Estimation of Speckle Variance in SAR Images: Simulation Results and Verification for Real-Life Data

Abramov, Sergey; Abramova, Victoriya; Ponomarenko, Nikolay N.; Vozel, Benôıt; Chehdi, Kacem; Егиазарян, Карен; Astola, Jaakko

doi:10.5772/57040

Cited by 18 publications

(8 citation statements)

References 37 publications

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“…The result showed similar speckle properties of the real SAR data as in [36] and the simulation is also faster than the time domain methods.…”

Section: Discussionsupporting

confidence: 62%

“…The probability density function of speckle is related to image forming and the number of looks, and it is not always Gaussian [35]. After an examination of single-look SAR images by taking fragments (homogeneous regions) of them, Abramov et al [36] realized that since both components of complex-valued data of any fragments are Gaussian with approximately the same variance, their amplitude values obey the Rayleigh distribution [36].…”

Section: Generation Of the Speckled Sar Complex Image Of The Backgroundmentioning

confidence: 99%

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An Integrated Method for Simulation of Synthetic Aperture Radar (SAR) Raw Data in Moving Target Detection

Rahmanizadeh

Amini

2017

Remote Sensing

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SAR (Synthetic Aperture Radar) raw data simulation has a significant role in the evaluation of newly-proposed methods for the estimation of moving target parameters. The evaluation of methods in different cases emphasizes the importance of the need to have fast simulators. Using reverse SAR imaging methods for the raw data simulations has achieved good results in the simulation of the static targets, but for the simulation of moving targets these methods have a few shortcomings. In this paper, we propose a method to simulate a speckled scene with moving targets in the hybrid domain. First, the scene is simulated, including speckle, which is statistically in accordance with real SAR image behavior. Then, a reverse imaging algorithm (inverse chirp scaling) was applied on the scene to generate the SAR raw data. The moving target simulation was also done in the time-domain as the next step. Finally, the results from two prior steps were superposed to generate the SAR raw data with moving targets. All steps of the proposed method were evaluated separately. The speckle procedure was evaluated by comparing the speckled SAR image before the simulation and the image of the SAR simulated raw data. The results show similar variations in real and imaginary parts of these data. The correlation between the reflectivity map and the SAR images after the simulation was calculated and the obtained correlation coefficient was about 0.95 for different images. The final data were further analyzed for the displacement of moving targets' positions. The results show similar displacement between moving target SAR raw data with a background and without a background.

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“…The result showed similar speckle properties of the real SAR data as in [36] and the simulation is also faster than the time domain methods.…”

Section: Discussionsupporting

confidence: 62%

Section: Generation Of the Speckled Sar Complex Image Of The Backgroundmentioning

confidence: 99%

An Integrated Method for Simulation of Synthetic Aperture Radar (SAR) Raw Data in Moving Target Detection

Rahmanizadeh

Amini

2017

Remote Sensing

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“…Such speckle has been modeled using methodology and algorithm described in [4]. Speckle values are dependent (correlated) only for neighbor pixels, i.e.…”

Section: Removal Of Spatially Correlated Specklementioning

confidence: 99%

“…Its main advantage has been already mentioned -speckle intensity reduces approximately proportionally to the number of looks and this partly simplifies the tasks of image segmentation, edge detection, target detection and recognition [1][2][3], etc. Meanwhile, SAR resolution becomes worse and speckle in multi-look images often possesses certain spatial correlation [4]. Thus, this opportunity (to acquire multi-look SAR images) should be exploited with care and a practical compromise is needed concerning a number of looks to be used.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Despeckling Efficiency of DCT-Based Filters Applied to SAR Images

Rubel¹,

Medeiros

2015

2015 International Conference on Distributed Computing in Sensor Systems

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This paper deals with one way to predict efficiency of despeckling for images acquired by a single-or multi-look synthetic aperture radar (SAR). A particular filter based on discrete cosine transform (DCT) and adapted to speckle characteristics is considered. Two quantitative criteria characterizing despeckling efficiency are analyzed. It is shown that even one parameter that can be calculated for image blocks sequentially or in parallel allows carrying out a rather accurate prediction. Moreover, such a prediction is possible for both spatially uncorrelated and correlated speckle.

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