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Radar sea clutter inhomogeneity in range is characterized by Doppler mean and spectrum width variations. We propose a new approach for robust statistical density estimation and segmentation of sea clutter Doppler spectrum. In each range cell, Doppler is characterized by a Toeplitz Hermitian Positive Definite covariance matrix that is coded in Poincaré's unit poly-disk and we use adaptation of standard...
This paper deals with a problem of dimensionality reduction for hyperspectral images using principal component analysis. Hyperspectral image reduction is improved by adding structural/spatial information to the spectral information, by means of mathematical morphology tools. It can be then useful for instance in supervised classification. The key element of the approach is the computation of a covariance...
We explore the problem of anomaly detection based on several one-dimensional projections. The main advantage of the proposed approach is that it does not require any covariance matrix estimation, allowing to compute spatial adaptive anomaly detection in small neighborhoods. Although this is contrary to common sense, theoretical results support the consistence of our approach when a large number of...
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