Simulation of spatially correlated clutter fields. (English) Zbl 1182.62185
Summary: Correlated \(\mathcal G\) distributions can be used to describe the clutter seen in images obtained with coherent illumination, as is the case of B-scan ultrasound, laser, sonar, and synthetic aperture radar (SAR) imagery. These distributions are derived using the square root of the generalized inverse Gaussian distribution for the amplitude backscatter within the multiplicative model. A two-parameter particular case of the amplitude \(\mathcal G\) distribution, called \(\mathcal G_A^0\), constitutes a modeling improvement with respect to the widespread \(\mathcal K_A\) distribution when fitting urban, forested, and deforested areas in remote sensing data.
This article deals with the modeling and the simulation of correlated \(\mathcal G_A^0\)-distributed random fields. It is accomplished by means of the inverse transform method, applied to Gaussian random fields with spatial correlation. The main feature of this approach is its generality, since it allows the introduction of negative correlation values in the resulting process, necessary for the proper explanation of the shadowing effect in many SAR images.
This article deals with the modeling and the simulation of correlated \(\mathcal G_A^0\)-distributed random fields. It is accomplished by means of the inverse transform method, applied to Gaussian random fields with spatial correlation. The main feature of this approach is its generality, since it allows the introduction of negative correlation values in the resulting process, necessary for the proper explanation of the shadowing effect in many SAR images.
MSC:
| 62M40 | Random fields; image analysis |
| 65C60 | Computational problems in statistics (MSC2010) |
| 62P12 | Applications of statistics to environmental and related topics |
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