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Proceedings Paper

Target detection and intelligent image compression
Author(s): Paul G. Ducksbury
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Paper Abstract

This novel approach uses automatic target detection together with compression techniques to achieve intelligent compression by exploiting knowledge of the image content. Two techniques have been experimented with one using horizontal-vertical (HV) partitioned quadtrees the other a variant of entropy called approximate entropy. The object masks that are generated using either of the techniques (or indeed other feature detectors) effectively cue potential areas of interest for subsequent encoding using two 'intelligent' image compression techniques. In the first approach, lossless compression algorithms can be applied to regions of interest within the images so that their statistical properties can be preserved to allow detailed analysis or further processing while the remainder of the image can be compressed with lossy algorithms. The degree of lossy compression is dependent both on the information content as well as the bandwidth requirement. In the second approach a wavelet-based decomposition is applied in which selective destruction of wavelet coefficients is performed outside the cued areas of interest (in effect concentrating the wavelets in required areas) prior to the encoding with a version of the progressive SPIHT encoder. Results will illustrate how both these approaches can be used for the detection and compression of airborne reconnaissance imagery.

Paper Details

Date Published: 17 August 2000
PDF: 12 pages
Proc. SPIE 4050, Automatic Target Recognition X, (17 August 2000); doi: 10.1117/12.395597
Show Author Affiliations
Paul G. Ducksbury, Defence Evaluation and Research Agency Malvern (United Kingdom)


Published in SPIE Proceedings Vol. 4050:
Automatic Target Recognition X
Firooz A. Sadjadi, Editor(s)

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