Paper
13 July 2000 Adaptive threshold-based spatio-temporal filtering techniques for detection of small targets
Venkateswarlu Ronda, Wei Lee New, M. J. Tan, Meng Hwa Er
Author Affiliations +
Abstract
There are several methods reported in the literature for detecting dim targets against slowly moving clutter. However, each method has its own advantages and disadvantages. The challenge lies in reducing the false alarm rate to an acceptable level. Choosing a threshold for achieving constant false alarm rate is always a tricky problem. Too less a threshold may ensure detection of target pixels. But this will result in with too many false targets, which limit the performance of the post- processor to trace out target paths. Too high threshold results in fewer false alarms but the targets also may miss out, creating a problem in establishing track record of targets. These contradicting issues demand a via-media solution to improve the overall concept of CFAR for the detection of dim point-targets in the presence of the evolving clouds and heavy background clutter. The adaptive threshold is based on random and correlated noises of the incoming image sequence. The incoming frames of data are processed by adaptive threshold and accumulated recursively. The post-processor with built-in flexibility checks for validity of target paths. This paper presents an improvement over our paper presented at SPIE, Denver duing July 1999. The algorithm has been tested with the available database and the results are very promising.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Venkateswarlu Ronda, Wei Lee New, M. J. Tan, and Meng Hwa Er "Adaptive threshold-based spatio-temporal filtering techniques for detection of small targets", Proc. SPIE 4048, Signal and Data Processing of Small Targets 2000, (13 July 2000); https://doi.org/10.1117/12.392012
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KEYWORDS
Target detection

Detection and tracking algorithms

Digital filtering

Signal processing

Data processing

Infrared radiation

Clouds

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