Wavelet-based target detection using multiscale directional analysis

Bradley J. Chambers; William D. Reynolds Jr.; Derrick S. Campbell; Darius K. Fennell; Rashid Ansari

doi:10.1117/12.720985

9 May 2007 Wavelet-based target detection using multiscale directional analysis

Bradley J. Chambers, William D. Reynolds Jr., Derrick S. Campbell, Darius K. Fennell, Rashid Ansari

Proceedings Volume 6566, Automatic Target Recognition XVII; 656608 (2007) https://doi.org/10.1117/12.720985
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

Efficient processing of imagery derived from remote sensing systems has become ever more important due to increasing data sizes, rates, and bit depths. This paper proposes a target detection method that uses a special class of wavelets based on highly frequency-selective directional filter banks. The approach helps isolate object features in different directional filter output components. These components lend themselves well to the application of powerful denoising and edge detection procedures in the wavelet domain. Edge information is derived from directional wavelet decompositions to detect targets of known dimension in electro optical imagery. Results of successful detection of objects using the proposed method are presented in the paper. The approach highlights many of the benefits of working with directional wavelet analysis for image denoising and detection.

Citation Download Citation

Bradley J. Chambers, William D. Reynolds Jr., Derrick S. Campbell, Darius K. Fennell, and Rashid Ansari "Wavelet-based target detection using multiscale directional analysis", Proc. SPIE 6566, Automatic Target Recognition XVII, 656608 (9 May 2007); https://doi.org/10.1117/12.720985

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