Hyperspectral target detection in noisy environment using wavelet filter and correlation based detector

Erol Sarigul; M. S. Alam

doi:10.1117/12.820312

4 May 2009 Hyperspectral target detection in noisy environment using wavelet filter and correlation based detector

Erol Sarigul, M. S. Alam

Proceedings Volume 7335, Automatic Target Recognition XIX; 73350F (2009) https://doi.org/10.1117/12.820312
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

In this paper, we propose an algorithm for detecting man made targets in hyperspectral imagery using correlation based detection after wavelet domain filtering. In the proposed method, each spectral pixel in noisy hyperspectral data cube is filtered by wavelet domain filtering. Wavelet domain filtering looks at every spectral pixel as noisy signal and filter out noise through wavelet shrinkage based method. Then correlation between the provided target spectral signature and spectral signal from data cube is calculated. The algorithm scans each pixel in data cube then calculates correlation with target signature. The process yields correlation image. Applying threshold operation for correlation image provides detection image. The detection performance of the algorithm is tested with several hyperspectral datasets. Using ROC analysis and comparing with ground truth image, it is observed that wavelet based filtering provides better detection performance for noisy data. The simulation results indicate that the proposed algorithm efficiently detects object of interest in all datasets.

Citation Download Citation

Erol Sarigul and M. S. Alam "Hyperspectral target detection in noisy environment using wavelet filter and correlation based detector", Proc. SPIE 7335, Automatic Target Recognition XIX, 73350F (4 May 2009); https://doi.org/10.1117/12.820312

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KEYWORDS

Wavelets

Detection and tracking algorithms

Denoising

Optical filters

Signal processing

Hyperspectral imaging

Sensors

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