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Wavelet Based SAR Speckle Reduction and Image Compression

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dc.contributor.author Odegard, Jan E.
Guo, Haitao
Lang, Markus
Burrus, C. Sidney
Wells, R.O.
Novak, L.M.
Hiett, M.
dc.creator Odegard, Jan E.
Guo, Haitao
Lang, Markus
Burrus, C. Sidney
Wells, R.O.
Novak, L.M.
Hiett, M.
dc.date.accessioned 2007-10-31T00:56:50Z
dc.date.available 2007-10-31T00:56:50Z
dc.date.issued 1995-04-01
dc.date.submitted 1995-04-01
dc.identifier.uri http://hdl.handle.net/1911/20171
dc.description Conference Paper
dc.description.abstract This paper evaluates the performance of the recently published wavelet based algorithm for speckle reduction of SAR images. The original algorithm, based on the theory of wavelet thresholding due to Donoho and Johnstone, has been shown to improve speckle statistics. In this paper we give more extensive results based on tests performed at Lincoln Laboratory (LL). The LL benchmarks show that the SAR imagery is significantly enhanced perceptually. Although the wavelet processed data results in an increase in the number of natural clutter false alarms (from trees etc.) an appropriately modified CFAR detector (i.e., by clamping the estimated clutter standard deviation) eliminates the extra false alarms. The paper also gives preliminary results on the performance of the new and improved wavelet denoising algorithm based on the shift invariant wavelet transform. By thresholding the shift invariant discrete wavelet transform we can further reduce speckle to achieve a perceptually superior SAR image with ground truth information significantly enhanced. Preliminary results on the speckle statistics of this new algorithm is improved over the classical wavelet denoising algorithm. Finally, we show that the classical denoising algorithm as proposed by Donoho and Johnstone and applied to SAR has the added benefit of achieving about 3:1 compression with essentially no loss in image fidelity.
dc.language.iso eng
dc.subject Temporary
dc.subject.other Wavelet based Signal/Image Processing
dc.title Wavelet Based SAR Speckle Reduction and Image Compression
dc.type Conference paper
dc.date.note 2004-11-10
dc.citation.bibtexName inproceedings
dc.date.modified 2004-11-10
dc.contributor.org Digital Signal Processing (http://dsp.rice.edu/)
dc.contributor.org CML (http://cml.rice.edu/)
dc.subject.keyword Temporary
dc.citation.volumeNumber 2
dc.citation.pageNumber 17-21
dc.citation.conferenceName SPIE Symp. OE/Aerospace Sensing and Dual Use Photonics, Algorithm for Synthetic Aperture Radar Image
dc.type.dcmi Text
dc.identifier.citation J. E. Odegard, H. Guo, M. Lang, C. S. Burrus, R. Wells, L. Novak and M. Hiett, "Wavelet Based SAR Speckle Reduction and Image Compression," vol. 2, pp. 17-21, 1995.

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  • ECE Publications [1048 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.