Visiontek PhotoMatrix-SAT remote sensing image cluster processing system PhotoMatrix-SAT
PhotoMatrix-SAT is a cluster software independently developed by Visiontek for large-scale comprehensive processing of satellite images. It is not only compatible with all common satellite images on the market, but also has high-precision aerial three operations capabilities and powerful cluster data processing performance. One-click full-automatic production of large-scale image empty three, DSM and DOM products.
Compared with common satellite image processing software on the market, the system has a series of advantages such as good compatibility, easy operation, comprehensive functions, high degree of automation, and cluster operation support.
Excellent data compatibility
Support processing all common domestic and foreign satellite image data on the market, including resource 3, Gaofen-1, Gaofen-2, Tianhui Satellite, ALOS, SPOT5, IKONOS, WorldView I/II, P5, GeoEye and other image data formats .
Convenient data organization ability
The system has convenient image data organization capabilities, can support a variety of flexible and fast engineering creation methods, and automatically recognizes and divides stereo pairs and co-orbit images after importing data. At the same time, it organizes exclusive satellite image formats according to the types of satellite images. It is convenient for special processing and later expansion.
One-click processing flow
The system is easy to operate and has a high degree of automation. It can automatically complete data processing operations such as satellite image matching turning point, adjustment orientation, DSM matching, orthorectification, image fusion, etc., without manual intervention in the whole process.
High performance remote sensing image space three processing
The system supports diversified matching and orientation methods of satellite images with reference DOM, reference DEM, and control points as reference data, as well as a variety of data source hybrid regional network adjustments. At the same time, users can perform comprehensive point editing operations on connection points and control points. And manually add weight constraints, so that the system's mapping accuracy can be higher than the provided reference image. If a certain accuracy of the reference image is provided, the accuracy can be controlled within one pixel.
In addition, the system has built-in comprehensive SRTM data, and the system can automatically call SRTM for uncontrolled adjustment when the reference DEM is missing.
Multi-data source mixed regional network adjustment
Large-scale satellite image DSM and DEM production
After the satellite image space three is completed, the system quickly realizes the DSM matching of the stereo image pair through the virtual scene, and outputs the large-scale satellite image DSM results. At the same time, the DEM is generated through terrain filtering, and the satellite image DEM is edited, spliced and cropped. , Format conversion and a series of operations.
Satellite image DSM results Partial zoom in of satellite image DSM results
Massive satellite image DOM output
The system uses multi-core, multi-threading and graphics card GPU computing to perform orthorectification on massive multi-source remote sensing images, and performs intelligent color uniformization based on the geographic information and color information of the template image, effectively controlling color distortion, noise, etc. after fusion It also supports fine editing of DOM results to generate excellent satellite image orthographic results.
Efficient cluster operation mode support
The system has a fully automatic task allocation and management mechanism, which can automatically divide and publish node data transmission and image processing tasks according to the cluster nodes and node working status, and further optimize the cluster operation mode, so that the cluster operation mode and the stand-alone operation mode are basically maintained Consistent, and the manual division of task areas has been added to further enhance the efficiency of cluster operations.
Automatic/manual cluster task division Cluster task management