- Java 11 platform updates
- Image Handling Improvements
- FMV variable frame rate support
HyperVise: v1 Build 2
HyperVISE, developed by LPA Systems, Inc., supplies image analysis capabilities for Multi/Hyperspectral imagery. HyperVISE is designed to provide non-scientific users with the ability to use high performance image analysis techniques without full understanding of complex algorithms. HyperVISE is compatible with GV™3.0 build 940f and up. Features include:
- Band Reduction - presents the user with a set of rudimentary choices to reduce the data set size by eliminating bands in the image.
- Band Aggregation – creates a new image based on known techniques for combining bands of a Multi/Hyperspectral image to enhance or suppress specific features of an image.
- Reed-Xiaoli (RX) Anomaly Detector - identifies pixels that contain spectral information significantly different from the specified reference background.
- Spectral Match Filter – identifies portions of an image that are similar to a given spectral signature.
- Constant False Alarm Rate (CFAR) Automatic Target Cuer – applied to the Reed-Xiaoli or Spectral Match Filter magnitude map output to highlight specific portions of the image for further investigation.
- Empirical Line Method (ELM) Atmospheric Correction – capability that allows users to eliminate the effects of the atmosphere in an image.
- Pixel Classifier – utilizes K-Means Pixel Classification to categorize similar-pixels in a scene.
- Local Spectral Signature Library – allows users to use the SMF algorithm with spectral signatures from existing libraries or other images after the image has been atmospherically corrected.
- Spectral Signature Utility – allows users to quickly view and compare spectral values.