Over the course of several years the NRL SeaLab group has been developing a suite of software applications for analyzing SAR imagery referred to as the NRL SAR Workbench, and providing limited distribution of the software package to interested parties. This suite of tools are software applications with a graphical user interface (GUI) written in the Java programming language that provide visual displays of SAR images, interactive selection of areas of interest, and tools for processing and analysis of those selected regions. The image processing, visual color rendering, and analysis tools are written in the C programming language and are called from the Java source code as C compiled executables. Through work performed by NRL, its contractor CPI, and a MITRE consultant (Simplex, LLC), the NRL SAR Workbench was extended to include a polarimetric SAR processing capability. The POLSAR processing features were implemented via the addition of 3 panels organized into Image Display, Classification, and Individual Tools capabilities.
Image Display Panel
The Image Display panel provides for easy viewing of POLSAR imagery stored as scattering matrix (S-matrix) or covariance matrix data that are color rendered as red, green, and blue (RGB) images. Arbitrary selection of the polarimetric image components is available for the RGB channels, clipping and scaling of the imagery to enhance display, as well as transformations between polarimetric bases (circular, linear, and Pauli). Processing can be limited to any selected area of interest within the image.
The classification panel provides an end-to-end sequence of processing steps that are commonly performed in classifying targets within POLSAR imagery: construction of covariance matrices, their initial spatial averaging (rebin), spatial filtering of the imagery, a subsequent spatial averaging, and then (finally) application of a target decomposition algorithm to identify scene elements within the imagery. Covariance matrices can be constructed for 2, 3, and 4 polarimetric components in linear, Pauli, and circular polarimetric bases. Spatial filtering was implemented for a Lee filter. Several target decomposition algorithms were implemented as classification options for the end user: Cloude-Pottier, Freeman-Durden, Yamaguchi, and Wishart. The Freeman-Durden and Yamaguchi classifiers include corrections for polarization orientation angle before applying the target decomposition. This correction removes look-dependent rotations of ground targets that can produce cross-pol contamination in the covariance matrix, thereby leading to incorrect estimates of double bounce, volume, and surface scattering contributions. Target decompositions of the POLSAR imagery can be limited to any selected area of interest within the image. An example Yamaguchi target decomposition of the Radar Satellite 2 (RADARSAT-2) image of Norfolk, VA is shown in Figure 1. Vegetation appears as green, bodies of water as blue, and buildings and bridges in red and magenta.
Individual Tools Panel
The individual tools panel provides the user with the option of performing selected processing operations on the POLSAR imagery. Available tools are the construction of a covariance matrix from S-matrix data, eigenvalue/eigenvector decomposition of a covariance matrix, spatial averaging, spatial filtering, classification algorithms, and basis transformations between any one of a variety of polarimetric bases: linear, Pauli, and circular. Options are available to export the results as color rendered RGB images in one of two file formats: the native file format developed for use within SeaLab, and in Hierarchical Data Format (HDF).
SAR Data Viewer
The SAR Data Viewer (SDV) is a companion stand-alone tool to NRL SAR Workbench that provides for interactive visual display of SAR imagery. SDV provides a host of capabilities, including brightness and contrast control, zoom, a line profile plot along a chosen path, histograms of areas of interest, and animations of sequences of SAR images stored as color rendered images in HDF. To fully exploit SDV's capabilities, CPI modified SAR Workbench to write the color rendered images of the input and output single look complex POLSAR data as a sequence of two images to the generated HDF files. This provided the capability to interactively switch between visual displays of the input and processed output POLSAR imagery within SDV to facilitate comparison of the results. An example is shown of a RADARSAT-2 image of Norfolk, VA that is 5384×3572 in azimuth and range for which the Cloude-Pottier target decomposition has been performed. The initial image displayed by SDV is the covariance matrix of the quadpol POLSAR data (Figure 2), while the second is the resulting target decomposition (Figure 3). Note that the Cloude-Pottier classification enhances the pixels of vegetation to a more prominent green color. It also more clearly delineates the bodies of water by blue, and provides for a much greater accentuation of the buildings shown in red.
Computational Efficiency, Supported Platforms, and File Formats
Particular attention has been paid in designing all POLSAR applications to handle processing of large images within the memory limitations of the computer platform. SAR Workbench is being supported by NRL for both Linux and Windows operating systems. SAR Workbench provides options for the import of a variety of image file formats, which include: Geographic Tagged Image File Format (GeoTIFF), RADARSAT Tagged Image File Format (TIFF), Sony Raw Image File (SRF), and TerraSAR-X (TSX).