Proceedings of the International Conference
I W S S I P   2005
12th INTERNATIONAL WORKSHOP ON SYSTEMS, SIGNALS & IMAGE PROCESSING

22 - 24 September 2005, Chalkida Greece
 
(from Chapter 1: Invited Addresses and Tutorials on Signals, Coding, Systems and Intelligent Techniques)

 Full Citation and Abstract

0 Title: Context based quantization using Bayesian inference
  Author(s): Dušan Gleich, Mihai Datcu
  Address: Remote Sensing Institute, German Aerospace Center, Oberpfaffenhofen, 82234 Weßling
dusan.gleich @ dlr.de, mihai.datcu @ dlr.de
  Reference: SSIP-SP1, 2005  pp. 459 - 462
  Abstract/
Summary
This paper presents a transformed-based compression of high resolution Synthetic Aperture Radar (SAR) images using wavelet transformation. SAR images are corrupted by multiplicative noise called speckle. To achieve higher compression ratio, this noise is firstly removed and denoised image is compressed. To remove speckle from SAR images a Bayesian filter in wavelet domain is developed. Lossy quantization is implemented using Bayesian theory in order to predict observed wavelet coefficient using inter and intra-scale dependencies in wavelet domain. The predicted indices are encoded. The signal-to noise ratio of reconstructed images and achieved compression ratios are compared with the state-of-the-art compression methods applied to the SAR images with resolution of one meter.
 
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