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Proceedings Paper

The design of wavelets for image enhancement and target detection
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Paper Abstract

Detecting dim targets in infrared imagery remains a challenging task. Several techniques exist for detecting bright, high contrast targets such as CFAR detectors, edge detection, and spatial thresholding. However, these approaches often fail for detection of targets with low contrast relative to background clutter. In this paper we exploit the transient capture capability and directional filtering aspect of wavelets to develop a wavelet based image enhancement method. We develop an image representation, using wavelet filtered imagery, which facilitates dim target detection. We further process the wavelet-enhanced imagery using the Michelson visibility operator to perform nonlinear contrast enhancement prior to target detection. We discuss the design of optimal wavelets for use in the image representation. We investigate the effect of wavelet choice on target detection performance, and design wavelets to optimize measures of visual information on the enhanced imagery. We present numerical results demonstrating the effectiveness of the approach for detection of dim targets in real infrared imagery. We compare target detection performance to performance obtained using standard techniques such as edge detection. We also compare performance to target detection performed on imagery enhanced by optimizing visual information measures in the spatial domain. We investigate the stability of the optimal wavelets and detection performance variation, across perspective changes, image frame sample (for frames extracted from infrared video sequences), and image scene content types. We show that the wavelet-based approach can usually detect the targets with fewer false-alarm regions than possible with standard approaches.

Paper Details

Date Published: 29 April 2009
PDF: 12 pages
Proc. SPIE 7351, Mobile Multimedia/Image Processing, Security, and Applications 2009, 735103 (29 April 2009); doi: 10.1117/12.816135
Show Author Affiliations
Stephen DelMarco, BAE Systems (United States)
Sos Agaian, The Univ. of Texas at San Antonio (United States)


Published in SPIE Proceedings Vol. 7351:
Mobile Multimedia/Image Processing, Security, and Applications 2009
Sos S. Agaian; Sabah A. Jassim, Editor(s)

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