Int. J. of Wireless and Mobile Computing   »   2015 Vol.8, No.3

 

 

Title: Motion estimation and spatial-temporal filter-based infrared small target detection algorithm

 

Authors: Zhonghua Wang; Yuan Liao; Qingping Liu; Chunyong Li

 

Addresses:
School of Information and Engineering, Nanchang Hangkong University, Nanchang, Jiangxi Province 330063, China; Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang, Jiangxi Province, 330063, China
School of Information and Engineering, Nanchang Hangkong University, Nanchang, Jiangxi Province 330063, China; Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang, Jiangxi Province, 330063, China
School of Information and Engineering, Nanchang Hangkong University, Nanchang, Jiangxi Province 330063, China; Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang, Jiangxi Province, 330063, China
Department of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China

 

Abstract: Under the effect of solar variation, atmospheric attenuation and thermal radiation distribution, the grey value of interference source is close to or equal to the target grey value. With the distance between the imaging system and the target being very long, the target is dotted or mottled in the image. In addition, the target motion is usually unknown and abrupt. All these factors cause the negative effect of small target detection. In this paper, we present a motion estimation and spatial-temporal filter-based algorithm to detect infrared small targets under complex background. The algorithm is divided into three steps: (1) researching the image transformation technology from greyscale pattern to entropy pattern; (2) studying the anisotropic smoothing and local constraint criterion of entropy flow; and (3) introducing spatial-temporal filter for detecting small targets through energy accumulation and trial search of targets. Compared to other methods, experimental results indicate that the proposed method can robustly detect small targets under complicated background.

 

Keywords: entropy flow; motion estimation; spatial-temporal filters; infrared targets; small target detection; image transformation; greyscale pattern; anisotropic smoothing; local constraints; small targets; energy accumulation; trial search; infrared imaging; solar variation; atmospheric attenuation; thermal radiation.

 

DOI: 10.1504/IJWMC.2015.069388

 

Int. J. of Wireless and Mobile Computing, 2015 Vol.8, No.3, pp.256 - 261

 

Submission date: 12 Jul 2014
Date of acceptance: 03 Sep 2014
Available online: 13 May 2015

 

 

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