Hardware Implementation of Hyperspectral Data Compression
The invention comprises a real-time wideband compressor system for multi-dimensional data that is composed of parallel compression engines and a central high-speed network switch. The CSA developed this hardware system for on-board, real-time compression of hyperspectral data prior to transmission from spacecraft to the Earth.
The invention includes two hyperspectral data compression techniques for use on board a satellite, for real-time data compression. These operate on the 2-D focal plane frame of hyperspectral data, the cross-track line of ground samples (pixels), each with its own spectral vector, sensed at a given moment. The two data compression techniques are based on innovative hyperspectral data compression techniques that were previously developed for software implementation: Successive Approximation Multi-Stage Vector Quantization (SAMVQ) and Hierarchical Self-Organizing Cluster Vector Quantization (HSOCVQ).
A compression engine is a stand-alone autonomous machine that implements either the SAMVQ or the HSOCVQ technique to compress a sub-set of hyperspectral imagery. A codevector trainer is the key component of a compression engine. In the development of a real-time data compressor, the implementation of vector distance calculation is critical, as it dominates the overall performance of the compression system. Two innovative architectures for computing vector distance are provided.
The invention has application for any sensor that collects three-dimensional data, in which the spectral dimension and one spatial dimension form a 2-D focal plane frame for data and the other spatial dimension varies with time (as in the case of a satellite moving over the Earth or a conveyor system moving under a sensor array), and for which the rate of data collection exceeds the capabilities of the available data transmission and/or data analysis. This system for real-time data compression and transmission provides a solution for rapid, real-time hyperspectral data analysis and spectral/spatial feature recognition.
The Business Opportunity
The invention has direct application to the collection of hyperspectral datasets from spaceborne or airborne remote sensing platforms. The technology will interest companies that provide hyperspectral data collection systems or data collection services to end-users.
The invention not only overcomes these limitations, but requires smaller computations, which contributes to minimizing the computational cost of performing a simulation. The proposed algorithm has application in such simulators, in that it facilitates both speed and accuracy in simulating complex dynamic systems in real-time.
The technology will also be of interest to companies and R&D organizations that are developing real-time hyperspectral monitoring and analysis systems for process control, inspection and quality control.
Technology Transfer Details
These technologies are available for licensing.
The business opportunity may be referred to by its CSA case ID: 50690-50691-50692
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- Qian, S.-E., M. Bergeron, I. Cunningham, L. Gagnon and A. Hollinger, "Near Lossless Data Compression On-board a Hyperspectral Satellite," Institute of Electrical and Electronics Engineers (IEEE), Transactions on Aerospace and Electronic System, Vol. 42, No. 3, pp. 851-866, July 2006.
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- Manak, D., S.-E. Qian, A. Hollinger and D. Williams, "Efficient Hyperspectral Data Compression using vector Quantization and Scene Segmentation," Canadian Journal of Remote Sensing, Vol. 24, No. 2, pp. 133-143, June 1998.
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- Number: 6,798,360
- Number: 7,551,785
- Number: 7,801,365
- Number: 7,251,376
- Status: Issued patents
- Source: United States Patent and Trademark Office (USPTO)
- Number: 1642238 (A1)
- Number: EP1642237 (A1)
- Status: Issued patents
- Number: EP1665077 (A2)
- Status: Pending patent application
- Source: European Patent Office (EPO)
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