Look-direction bias in a single-look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look-direction bias. The two important approaches for reducing look-direction bias and integration of multiple SAR data sets are: Principal Component Analysis (PCA); and Wavelet Transform (WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS's airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integrating more than two layers of digital image data. When only two sets of SAR data are available, the PCA technique requires at least one more set of auxiliary data for proper rendition of fine surface features. The WT processing approach of SAR data integration utilizes the property that decomposes images into both an approximated image (low frequencies) characterizing the spatially large and relatively distinct structures and a detailed image (high frequencies) in which the information on detailed fine structures is preserved. The test results with the ERS-1 and CCRS's C-SAR data indicate that the new WT approach is more robust than the PCA approach in enhancing fine details of the multiple SAR images.
|Number of pages||6|
|Journal||Canadian Journal of Remote Sensing|
|Publication status||Published - 1994 Sep|
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)