Target Detection Using a Wavelet-Based Fractal Scheme

<p>In this thesis, a target detection technique using a rotational invariant wavelet-based scheme is presented. The technique is evaluated on Synthetic Aperture Rader (SAR) imaging and compared with a previously developed fractal-based technique, namely the extended fractal (EF) model. Both techniques attempt to exploit the textural characteristics of SAR imagery. Recently, a wavelet-based fractal feature set, similar to the proposed one, was compared with the EF feature for a general texture classification problem. The wavelet-based technique yielded a lower classification error than EF, which motivated the comparison between the two techniques presented in this paper. Experimental results show that the proposed techniques feature map provides a lower false alarm rate than the previously developed method.</p>

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical Engineering

Year

2006

Author dc:creator

• Stein, Gregory W.

Contributors dc:contributor

• Charalampidis, Dimitrios
• Bourgeois, Edit
• Chen, Huimin

• Target Detection
• Wavelet
• Fractal

Repository record dc:identifier

https://scholarworks.uno.edu/td/437

OAI identifier oai:identifier

oai:scholarworks.uno.edu:td-1458