Impact of wavelet types on image data characteristics during compression

Daniel S. Myers; David K. Melgaard; Raymond H. Byrne; Phillip J. Lewis

doi:10.1117/12.801377

3 September 2008 Impact of wavelet types on image data characteristics during compression

Daniel S. Myers, David K. Melgaard, Raymond H. Byrne, Phillip J. Lewis

Proceedings Volume 7075, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI; 707505 (2008) https://doi.org/10.1117/12.801377
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

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.

Citation Download Citation

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); https://doi.org/10.1117/12.801377

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