Spatial-temporal filtering method based on kernel density estimation in suppressing background clutter

Yuexin Tian; Yinghui Liu; Kun Gao; Yuwen Shu; Guoqiang Ni

doi:10.1117/12.2072618

24 November 2014 Spatial-temporal filtering method based on kernel density estimation in suppressing background clutter

Yuexin Tian, Yinghui Liu, Kun Gao, Yuwen Shu, Guoqiang Ni

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93012F (2014) https://doi.org/10.1117/12.2072618
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

A temporal-spatial filtering algorithm based on kernel density estimation structure is presented for background suppression in this paper. The algorithm can be divided into spatial filtering and temporal filtering. Smoothing process is applied to the background of an infrared image sequence by using the kernel density estimation algorithm in spatial filtering. The probability density of the image gray values after spatial filtering is calculated with the kernel density estimation algorithm in temporal filtering. The background residual and blind pixels are picked out based on their gray values, and are further filtered. The algorithm is validated with a real infrared image sequence. The image sequence is processed by using Fuller kernel filter, Uniform kernel filter and high-pass filter. Quantitatively analysis shows that the temporal-spatial filtering algorithm based on the nonparametric method is a satisfactory way to suppress background clutter in infrared images. The SNR is significantly improved as well.

Citation Download Citation

Yuexin Tian, Yinghui Liu, Kun Gao, Yuwen Shu, and Guoqiang Ni "Spatial-temporal filtering method based on kernel density estimation in suppressing background clutter ", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012F (24 November 2014); https://doi.org/10.1117/12.2072618

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KEYWORDS

Image filtering

Infrared imaging

Image processing

Infrared radiation

Linear filtering

Optical filters

Detection and tracking algorithms

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