Synthetic aperture radar (SAR) image compression using the wavelet transform

In this thesis, two key characteristics of Synthetic Aperture Radar (SAR) images, namely their speckle noise and varied image contents are addressed. We develop a selective soft-thresholding method and a multi-rate compression scheme to compress SAR images more efficiently, using the wavelet transform to accomplish both the noise smoothing and image compression tasks.; We initially approach the SAR image compression problem by studying the effects of SAR image characteristics using standard compression techniques, such as Joint Photographic Expert Group (JPEG) method, the Efficient Pyramidal Image Coder (EPIC) and the Embedded Zerotree Wavelet (EZW) coder. We find that speckle noise tends to break the inter-pixel correlation in SAR images and thus has negative effects on compression. In order to compress SAR images more efficiently, we need to smooth speckle noise and to enhance inter-pixel correlation prior to image compression. To this end, we develop a selective soft-thresholding method which refines Donoho's overall soft-thresholding method.; Another issue in SAR image compression is concerned with the varied scene contents within large-size SAR images. We propose a multi-rate compression scheme on top of the EZW algorithm. (Abstract shortened by UMI.)...