Results of registering syntheticapertureradar (SAR) images are presented. A set of reference (tie) points are specified in a target image and an iterative search performed to obtain the corresponding tie points in a...
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Results of registering syntheticapertureradar (SAR) images are presented. A set of reference (tie) points are specified in a target image and an iterative search performed to obtain the corresponding tie points in a source image. Registration error is computed for each tie point by estimating its translational misalignment. The set of tie point error vectors are subsequently used to update the registration transformation. This processing sequence is repeated until convergence. The registration algorithm converges to the correct transformation in all cases tried so far. Tests on SAR imagery with known misalignment indicate that the algorithm can achieve simultaneously rms errors of 0.01°, 0.03 pixel, and 0.01% in rotation, translation, and scale, respectively.
The recently introduced Phase Gradient Autofocus (PGA) algorithm is a non-parametric autofocus technique which has been shown to be quite effective for phase correction of syntheticapertureradar (SAR) imagery. This ...
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The recently introduced Phase Gradient Autofocus (PGA) algorithm is a non-parametric autofocus technique which has been shown to be quite effective for phase correction of syntheticapertureradar (SAR) imagery. This ...
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The recently introduced Phase Gradient Autofocus (PGA) algorithm is a non-parametric autofocus technique which has been shown to be quite effective for phase correction of syntheticapertureradar (SAR) imagery. This paper will show that this powerful algorithm can be executed at near real-time speeds and also be implemented in a relatively small piece of hardware. A brief review of the PGA will be presented along with an overview of some critical implementation considerations. In addition, a demonstration of the PGA algorithm running on a 7 inches × 10 inches printed circuit board containing a TMS320C30 digital signal processing (DSP) chip will be given. With this system, using only the 20 range bins which contain the brightest points in the image, the algorithm can correct a badly degraded 256×256 image in as little as 3 seconds. Using all range bins, the algorithm can correct the image in 9 seconds.
This paper describes a new gradient algorithm for enhancing linear features in syntheticapertureradarimagery. The algorithm is based on finding the maximum average gradient over a local window centered on a pixel. ...
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It has been suggested that syntheticapertureradar (SAR) images obtained from platforms such as SEASAT are subject to potential degradation by ionospheric-induced phase errors. This premise is based upon data from va...
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Speckle is a major cause of degradation in syntheticapertureradar (SAR) imagery. With the availability of fully polarimetric, high-resolution SAR data, it is possible to use the three complex elements (HH, Hv, vv) o...
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Speckle is a major cause of degradation in syntheticapertureradar (SAR) imagery. With the availability of fully polarimetric, high-resolution SAR data, it is possible to use the three complex elements (HH, Hv, vv) of the polarimetric scattering matrix to reduce this speckle. The optimal method of combining the elements of the scattering matrix to minimize image speckle is derived;the solution is shown to be a polarimetric whitening filter (PWF). For homogeneous clutter, this algorithm reduces the standard deviation-to-mean ratio of 4.8 dB (relative to that of a single-polarimetric-channel |HH|2 image);this is 1.9 dB better than the span algorithm. Also, a simulation of spatially correlated, K-distributed, fully polarimetric clutter is developed and is used to compare the optimal speckle reduction method with other, suboptimal methods. Finally, the target detection performance of span, single-channel |HH|2 data, and the PWF are compared with the optimal polarimetric detector.
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