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An improved algorithm for facet-based infrared small target detection

KEJIA YI1,2, TINGQUAN DENG1, TIANXU ZHANG2, JING GUAN2, JING HU2

Affiliation

  1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
  2. Laboratory for Multispectral Information Processing Technologies, Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 4

Abstract

The facet-based small target detection method is shown as robust and efficient, but it does not perform well in target preservation. In this paper an improved algorithm is proposed. The algorithm uses facet model to fit local intensity surface and detects potential bright and dark targets using extremum theory, then the zero-crossings of the second partial derivatives of the fitting function in each potential target’s neighborhood are found, the pixels inside the zero-crossing contour are restored to the potential target. In experiments involving typical infrared images target intensity distribution information is well preserved..

Keywords

Small target detection, Target preservation, Cubic facet model, Extremum theory, Zero-crossing.

Submitted at: Feb. 20, 2012
Accepted at: April 11, 2012

Citation

KEJIA YI, TINGQUAN DENG, TIANXU ZHANG, JING GUAN, JING HU, An improved algorithm for facet-based infrared small target detection, Journal of Optoelectronics and Advanced Materials Vol. 14, Iss. 3-4, pp. 298-303 (2012)