Title :
Image classification in complex spaces
Author_Institution :
Lockheed Martin Corp., Saint Anthony, MN, USA
Abstract :
Addresses issues related to classification of images in complex spaces. The image is represented in terms of phase and amplitude components. The classifier optimizes functions of joint real and imaginary conditional probability density functions. A bound on the total probability of errors in terms of Rayleigh quotient is derived and compared to the cases where a non-complex amplitude-only signal is used. Examples of application of the proposed approach on polarimetric radar imagery indicate several orders of magnitude improvement in performance.
Keywords :
image classification; radar imaging; radar polarimetry; Bayes classifiers; Fisher distance; Rayleigh quotient; amplitude components; complex spaces; conditional probability density functions; image classification; noncomplex amplitude-only signal; pattern recognition; phase components; polarimetric radar imagery; radar signal processing; total probability errors; Decision making; Image classification; Pattern recognition; Performance analysis; Probability density function; Radar applications; Radar imaging; Radar polarimetry; Radar remote sensing; Radar signal processing;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1026592
