@inproceedings{457da3e77026473db194c4fa524e9510,
title = "Spatial-temporal filtering method based on kernel density estimation in suppressing background clutter",
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.",
keywords = "Infrared background suppression, Kernel density estimation, Spatial-temporal filtering",
author = "Tian Yuexin and Liu Ying and Gao Kun and Shu Yuwen and Ni Guoqiang",
note = "Publisher Copyright: {\textcopyright} 2014 SPIE.; International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, IPTA 2014 ; Conference date: 13-05-2014 Through 15-05-2014",
year = "2014",
doi = "10.1117/12.2072618",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Gaurav Sharma and Fugen Zhou",
booktitle = "International Symposium on Optoelectronic Technology and Application 2014",
address = "United States",
}