Paper
25 July 2002 Target detection in hyperspectral images based on independent component analysis
Author Affiliations +
Abstract
The paper presents an algorithm based on Independent Component Analysis (ICA) for the detection of small targets present in hyperspectral images. ICA is a multivariate data analysis method that attempts to produce statistically independent components. This method is based on fourth order statistics. Small, man-made targets in a natural background can be seen as anomalies in the image scene and correspond to independent components in the ICA model. The algorithm described here starts by preprocessing the hyperspectral data through centering and sphering, thus eliminating the first and second order statistics. It then separates the features present in the image using an ICA based algorithm. The method involves a gradient descent minimization of the mutual information between frames. The resulting frames are ranked according to their kurtosis (defined by normalized fourth order moment of the sample distribution). High kurtosis valued frames indicate the presence of small man-made targets. Thresholding the frames using zero detection in their histogram further identifies the targets. The effectiveness of the method has been studied on data from the hyperspectral digital imagery collection experiment (HYDICE). Preliminary results show that small targets present in the image are separated from the background in different frames and that information pertaining to them is concentrated in these frames. Frame selection using kurtosis and thresholding leads to automated identification of the targets. The experiments show that the method provides a promising new approach for target detection.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stefan A. Robila and Pramod K. Varshney "Target detection in hyperspectral images based on independent component analysis", Proc. SPIE 4726, Automatic Target Recognition XII, (25 July 2002); https://doi.org/10.1117/12.477024
Lens.org Logo
CITATIONS
Cited by 32 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Independent component analysis

Target detection

Hyperspectral imaging

Detection and tracking algorithms

Hyperspectral target detection

Principal component analysis

Image processing

Back to Top