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Proceedings Paper

Small target detection from image sequences using recursive max filter
Author(s): Ken-Ichi Nishiguchi; Masaaki Kobayashi; Akira Ichikawa
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Paper Abstract

This paper presents a new method for detection of small moving targets from noisy image sequences using a recursive filter, which contains a local maximum filter in the feedback loop. Since all the procedures contained in this method can be implemented by fully parallel algorithm, this method can be realized by a neural network and real-time processing is possible for image sequences at high frame rates. First we investigate the performance of the method on the assumption that the targets move randomly in an image plane and the background noise is white both in time and space. The results show that the proposed method has the ability to suppress the background noise and enhances small moving targets, and that the targets are detected only by thresholding after the processing of the recursive filter. There can be other backgrounds such as clutters and stationary objects. It is also shown that the above method is applicable after preprocessing of conventional time difference method, and is able to suppress these backgrounds. Next we analyze the performance of the method using the property of order statistics. The performance measure is the output signal-to-noise ratio and is represented analytically as a function of input SNR and the parameters included in the method. Finally, the recursive filter is optimized using the result of the analysis.

Paper Details

Date Published: 1 September 1995
PDF: 14 pages
Proc. SPIE 2561, Signal and Data Processing of Small Targets 1995, (1 September 1995); doi: 10.1117/12.217676
Show Author Affiliations
Ken-Ichi Nishiguchi, Mitsubishi Electric Corp. (Japan)
Masaaki Kobayashi, Mitsubishi Electric Corp. (Japan)
Akira Ichikawa, Mitsubishi Electric Corp. (Japan)


Published in SPIE Proceedings Vol. 2561:
Signal and Data Processing of Small Targets 1995
Oliver E. Drummond, Editor(s)

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