Technology / Expertise
- Automated feature and pattern recognition algorithms for Remotely Sensed (RS) data; Object-based feature classification and extraction from RS data using spectral, spatial, and contextual information available in the imagery
- Advanced, automated pre-processing techniques such as topographic normalization, radiometric/temporal standardization, data gap detection (clouds, shadows, Landsat 7 ETM+ SLC-off anomaly), data gap filling, and under-shadow feature enhancement
- Novel algorithms for the rapid, automated processing of very large image databanks (e.g., NASA, NOAA, USGS, etc.) to produce usable information for everyday applications, models, and decision-making
- Classification and Change Detection algorithms based on probability theory
- Reprogrammable logic devices (e.g., FPGA) for image processing applications, including complex object-based applications
- Automated and semi-Automated tools for vector-to-raster and raster-to-vector data fusion/conflation
- Web-GIS and spatial database management systems (SDBMS) solutions for applicational users
- Custom Image Processing/GIS software to process, analyze, or add value to Remotely Sensed raster data and vector GIS data
- Guidance and direct aid to clients in optimizing Remotely Sensed and GIS data for use in operational decision support systems/models
- Turn-key system development and engineering including software and hardware components
- Novel, semi-automated and fully automated algorithms to process government and commercial RS/GIS data to a level useful for local, regional, federal, and commercial decision-makers in areas such as:
- Agriculture, Health, Defense, Forestry, Transportation, Public Utilities, and Environmental Monitoring, as well as for the planning and execution of image acquisition missions