Development of a demeaning filter for small object detection in infrared images

Hwal-Suk Lee; Seokkwon Kim; Je Hee Lee; Won-Chul Choi; Dong-Jo Park; Chang-Kyun Noh; NamHun Kang

doi:10.1117/12.819077

4 May 2009 Development of a demeaning filter for small object detection in infrared images

Hwal-Suk Lee, Seokkwon Kim, Je Hee Lee, Won-Chul Choi, Dong-Jo Park, Chang-Kyun Noh, NamHun Kang

Proceedings Volume 7335, Automatic Target Recognition XIX; 733513 (2009) https://doi.org/10.1117/12.819077
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

The demeaning filter detects a small object by removing a background with a mean filter as well as the covariance of an object and backgrounds. The factors considered in the design of the demeaning filter are the method of demeaning, which involves subtracting the local mean value from all pixel values, and the acquisition of templates for both the object and the background. This study compares the sliding window method and the grid method as a demeaning method, and studies the method of acquisition of an object template. Moreover, a method involving the use of previous frames, a mean filter, and an opening operation are studied in an effort to acquire a background template. Based on the results of this study, a practical design of a demeaning filter that is able to detect a small object in an IR image in real time is proposed. Experiment results demonstrate the superiority of the proposed design in detecting a small object following a 2-D Gaussian distribution even under severe zero-mean Gaussian noise.

Citation Download Citation

Hwal-Suk Lee, Seokkwon Kim, Je Hee Lee, Won-Chul Choi, Dong-Jo Park, Chang-Kyun Noh, and NamHun Kang "Development of a demeaning filter for small object detection in infrared images", Proc. SPIE 7335, Automatic Target Recognition XIX, 733513 (4 May 2009); https://doi.org/10.1117/12.819077

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