Application of pixel segmentation to the low rate compression of complex SAR imagery

This paper describes a technique to identify pixels within a subregion (chip) of a complex or detected SAR image which are to be losslessly compressed while the remainder of the image is subjected to a high compression ratio. This multi-modal compression is required for the intelligent low rate compression of SAR imagery, which addresses the problem of transmitting massive amounts of high resolution complex SAR data from a remote airborne sensor to a ground station for exploitation by an automatic target recognition (ATR) system, in a real time environment, over a narrow bandwidth. The ATR system results might then be presented to an image analyst who, using the contextual information from the SAR image, makes final target determination

Wavelet Compression of Complex SAR Imagery Using Complex- and Real-Valued Wavelets: A Comparative Study

While many synthetic aperture radar (SAR) applications use only detected imagery, dramatic improvements in resolution and employment of algorithms requiring complex-valued SAR imagery suggest the need for compression of complex data. Here, we investigate the benefits of using complex- valued wavelets on complex SAR imagery in the embedded zerotree wavelet compression algorithm, compared to using real-valued wavelets applied separately to the real and imaginary components. This compression is applied at low ratios (4:1-12:1) for high fidelity output. The complex spatial correlation metric is used to numerically evaluate quality. Numerical results are tabulated and original and decompressed imagery are presented as well as correlation maps to allow visual comparisons

Intelligent low rate compression of speckled SAR imagery

This paper describes a compression technique under development at Sandia National Laboratories for the compression of complex synthetic aperture radar (SAR) imagery at very low overall bit rates. The methods involved combine several elements of existing and new lossy and lossless compression schemes in order to achieve an overall compression ratio of large SAR scenes of at least 50:1, while maintaining reasonable image quality. It is assumed that the end user will be primarily interested in specific regions of interest within the image (called chips), but that the context in which these chips appear within the entire scene is also of importance to an image analyst. The term intelligent is used to signify an external cuer which locates the chips of interest

Lossless compression of synthetic aperture radar images

Synthetic Aperture Radar (SAR) has been proven an effective sensor in a wide variety of applications. Many of these uses require transmission and/or processing of the image data in a lossless manner. With the current state of SAR technology, the amount of data contained in a single image may be massive, whether the application requires the entire complex image or magnitude data only. In either case, some type of compression may be required to losslessly transmit this data in a given bandwidth or store it in a reasonable volume. This paper provides the results of applying several lossless compression schemes to SAR imagery