Motion estimation and spatial–temporal filter–based infrared small target detection algorithm. (2015)

• Record Type: Journal Article
• Authors: Wang, Zhonghua; Liao, Yuan; Liu, Qingping; Li, Chunyong
• Is Part Of: International journal of wireless and mobile computing. Volume 8:Number 3(2015)
• Page Start: 256
• Page End: 261
• Publication Date: 2015
• Subjects: 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; Mobile computing -- Periodicals; Wireless communication systems -- Periodicals; 004.6
• Languages: English
• ISSNs: 1741-1084

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.