Paper
5 July 1995 Optimized encoder design algorithm for joint compression and recognition
Jin-Woo Nahm, Mark J. T. Smith
Author Affiliations +
Abstract
Sensor data, such as SAR and FLIR images, are commonly transmitted from aircraft or satellites to airborne or ground stations for target detection and recognition processing. ATR algorithms are typically run at remote locations because they are very complex computationally, and require powerful computer resources. Rarely is unlimited channel bandwidth available for transmission. Thus one must also contend with delay-cost-quality tradeoff issues, which are often addressed by compressing data prior to transmission. Overall performance is largely restricted by the computational power of the on-board processor, since this limits the complexity and quality of the compression, which in turn affects the speed of transmission. Given some fixed level of computational power available for compression and transmission on board the aircraft, a useful technological improvement would be to have some level of on-board detection/recognition capability so that immediate action could be taken as appropriate. Toward this end, we introduce a method of joint compression and recognition for potential implementation on sensor-equipped aircraft. The algorithm is formulated to provide a level of immediate classification as a by-product of the compression, which in turn would provide the pilot with potential target information instantly.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jin-Woo Nahm and Mark J. T. Smith "Optimized encoder design algorithm for joint compression and recognition", Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); https://doi.org/10.1117/12.213021
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Cited by 1 scholarly publication.
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KEYWORDS
Computer programming

Automatic target recognition

Detection and tracking algorithms

Target detection

Image classification

Image compression

Target recognition

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