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3 September 2008 Impact of wavelet types on image data characteristics during compression
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We examine the effects of wavelet compression on target detection algorithms when the targets are single-pixel point sources modulated by the point-spread of an optical system. The experimental data combines frames collected from a multispectral sensor with simulated targets based on an Airy function. We studied several different types of wavelets and found that the Daubechies 2 wavelet resulted in the best overall target detection and fewest false alarms with increasing compression. Results show that wavelet compression may decrease pixel intensities, increase target signal-to-noise ratio, and reduce false detections. Consequently it may negatively affect target detection unless the detector is designed to take the decreased intensity into account.
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Daniel S. Myers, David K. Melgaard, Raymond H. Byrne, and Phillip J. Lewis "Impact of wavelet types on image data characteristics during compression", Proc. SPIE 7075, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI, 707505 (3 September 2008);

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