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SAR (synthetic aperture radar) images are strongly disturbed by speckle noises, which brings difficulty to the segmentation of the SAR images. Some model-based SAR image segmentation approaches (such as the Markov random field model, fractal model) are too complex and time consuming. We propose an new method to segment the SAR images fast in this paper. First we transform the original SAR intensity...
The framework of this study is focused on automatic fast recognition of agricultural interest for TerraSAR-X images. The intended goal is to label regions in an image as fast as possible, into classes significant for a given application, like crop classification. First, a filtering technique is applied to obtain the restored image. Then, two different methods of unsupervised segmentation are used...
This work proposes a novel speckle suppression method, called robust nonlinear wavelet diffusion. It shows that the log-transformed speckle can be approximated by Gaussian noise contaminated with long burst outliers. Consequently, we exploit this knowledge to design a speckle suppression filter within the framework of wavelet analysis. The outliers are removed by the combination of the robust-residual...
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