3D Data Compression Systems Based on Vector Quantization for Reducing the Data Rate of Hyperspectral Imagery
The next generation of satellite-based remote sensing instruments will produce an unprecedented volume of data. Imaging spectrometers, also known as hyperspectral imagers, are prime examples. They collect image data in hundreds of spectral bands simultaneously from the near ultraviolet through the short wave infrared, and are capable of providing direct identification of surface materials. A schematic diagram illustrating the concept of an imaging spectrometer is given in Fig.11. The volume and complexity of data produced by these instruments offers a significant challenge to downlink transmission and traditional image analysis methods. Since they produce 3-dimensional (3D) data cubes in which two dimensions correspond to spatial position and the third to wavelength, raw data rates can easily exceed the available downlink capacity or on-board storage capacity. Often, therefore, a portion of the data collected on board is discarded before transmission. This data reduction process may involve: 1) reducing the duty cycle, 2) reducing the spatial or spectral resolution, and 3) reducing the spatial or spectral range. Obviously, in such cases large amounts of information are lost.
KeywordsRoot Mean Square Error Compression Ratio Data Compression Vector Quantization Data Cube
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- 3.M. Morel et al, Envisat’s medium resolution imaging spectrometer, ESA bulltin No. 76:40–46 (1993).Google Scholar
- 6.N.M. Nasrabadi and Y. Feng, Vector quantization of images based upon the Kohonen self-organizing feature maps, Proc. IEEE Int. Conf. Neural Networks 101–108 (1988).Google Scholar
- 7.Shen-En Qian, Allan B. Hollinger, Dan Williams and Davinder Manak, Fast 3D data compression of hyperspectral imagery using vector quantization with spectral-feature-based binary coding, To be published in Optical Eng.Google Scholar
- 8.Shen-En Qian, Allan B. Hollinger, Dan Williams and Davinder Manak, A near lossless 3-dimensional data compression system for hyperspectral imagery using correlation vector quantization, 47th International Astronautical Congress, Beijing, China (1996).Google Scholar
- 9.Shen-En Qian, Allan B. Hollinger, Dan Williams and Davinder Manak, 3-Dimensional data compression of hyperspectral imagery using fast correlation vector quantization, To be published in IEEE trans on Geosci. & Remote Sensing.Google Scholar