Title :
A new approach to VQ-based compression and classification of sensor data
Author :
Barnes, Christopher F.
Author_Institution :
Tech. Res. Inst., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
The size and power resource constraints associated with the airborne platforms of various sensor systems require that sensor data be transmitted to ground based automatic target recognition (ATR) processing stations. However, the bandwidth limitations of feasible communication channels restrict the amount of data that can be reliably transmitted. This presentation gives an overview of a new technology that permits efficient clipping service on board the airframe that is based on the use of vector quantization (VQ). The new technology generates a mathematical decomposition of sensor data called “direct sum successive approximations” (DSSA). DSSA technologies permit low-level ATR functions to be combined with VQ data compression functions to form an intelligent clipping service
Keywords :
aerospace computing; aircraft instrumentation; image classification; image sensors; vector quantisation; VQ-based compression; airborne platforms; automatic target recognition; bandwidth limitations; classification; communication channels; data compression functions; direct sum successive approximation; ground based processing stations; intelligent clipping service; mathematical decomposition; power resource constraints; sensor data; vector quantization; Cancer detection; Decision support systems; Extraterrestrial measurements; Humans; Image sensors; Intelligent sensors; Sensor systems; Sonar detection; Space technology; Vector quantization;
Conference_Titel :
Aerospace and Electronics Conference, 1996. NAECON 1996., Proceedings of the IEEE 1996 National
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-3306-3
DOI :
10.1109/NAECON.1996.517657