## Abstract The aim of this work is to present a method for the segmentation of images based on local higher order statistics. The algorithm can be applied for the separation of objects from a texture background and the segmentation of textures. The proposed technique makes no use of a data bank an
Radar imaging using higher order statistics
β Scribed by P. Niemand; J. W. Odendaal
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 119 KB
- Volume
- 16
- Category
- Article
- ISSN
- 0895-2477
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β¦ Synopsis
In this article, it is proposed that fourth-order statistics are used for radar imaging rather than second-order statistics. The ad¨antages gained using higher order statistics are demonstrated for both con¨entional Fourier imaging as well as for subspace-based algorithms, e.g., MUSIC. The techniques are applied to simulated data as well as data measured in a compact range. Signals that with second-order statistics would be imbedded in noise can be detected using radar imaging based on higher order statistics.
π SIMILAR VOLUMES
Experimental impacting signals with unknown measurement noise are examined using third-order statistics blind deconvolution. The impulse impact signals are recovered and the estimation of the time between impacts improved. The procedure for obtaining the optimal inverse filter is addressed using obj