Polarimetric matched filter for coherent imaging

Abstract

In this paper we focus on image-contrast optimization between two rough-surface classes. Our approach is based strictly on polarimetric filtering, and therefore, no digital image-processing techniques are employed. The approach is tested on a complete polarimetric synthetic aperture radar (POL-SAR) image of the San Francisco Bay area. The data have been taken with the National Aeronautics and Space Administration – Jet Propulsion Laboratory CV-990L-band POL-SAR system, where eight real numbers (complex elements of a 2 × 2 polarization scattering matrix) are associated with each image pixel. Optimal transmitted polarizations (corresponding to maxima or minima of reflected energy) are found for each image pixel, and the results are analyzed statistically via a set of joint two-dimensional histograms. This is done for both of the rough-surface classes. The image response to the "optimal" incident polarization is then simulated digitally by adjusting the receiver polarization according to the modes of the histograms. The corresponding images are computed and displayed with significant image-contrast improvement.

Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics

“…Depending on the polarimetric signature of co-and cross-polarization channels, there appear stationary points of peaks, valleys, and saddle points of which the positions are inherent to scattering objects. Using these characteristic polarization states, polarimetric filters can be produced for image enhancement, contrast optimization, and classification e.g., [88][89][90][91]94,100,102,114].…”

Joint contrast optimization and object segmentation in active polarimetric images

“…Extensive research has been conducted to maximize the contrast between an object of interest and a background in target detection applications [3][4][5][6]. Most of these studies assumed that the polarimetric properties (i.e., the Mueller matrices) of the objects in the scene were known beforehand.…”