The design of Top-Hat morphological filter and application to infrared target detection

被引：255
作者：
Zeng, M [1 ]
Li, JX [1 ]
Peng, Z [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Sch Informat & Control, Inst Informat & Control, Shanghai 200030, Peoples R China
来源：
INFRARED PHYSICS & TECHNOLOGY | 2006年 / 48卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Top-Hat morphological filter; neural network; genetic algorithm;
D O I：
10.1016/j.infrared.2005.04.006
中图分类号：
TH7 [仪器、仪表];
学科分类号：
0804 ; 080401 ; 081102 ;
摘要：
Automatic detection and track for infrared target is of great significance in modern world. In this paper, two novel methods which can develop optimizing Top-Hat morphological filtering parameters are presented for spot target detection. One is based on neural network. Its structuring element is a two-layer feed-forward network which is trained by a mass of sample nets. It regards Top-Hat operation as a whole and one layer, and defines the node of the output layer as the maximum gray-scale image vector after Top-Hat operation. The other is based on genetic algorithm. It adopts the interval discretization code and new primary and secondary mood crossover and mutation. Experimental results show that the identified probability of images (SNR is about 2) can reach more than 98% by this method. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：67 / 76
页数：10
相关论文
共 13 条
[1]  
BIN Y, 2002, J IMAGE GRAPHICS, V1006
[2]   Some applications of morphological neural networks [J].
Graña, M ;
Raducanu, B .
IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS, 2001, :2518-2523
[3]  
GUO SZ, 2001, SOFT COMPUTATION MET
[4]   Morphological operators on the unit circle [J].
Hanbury, AG ;
Serra, J .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (12) :1842-1850
[5]  
HARVEY NR, 1994, IEE C GEN ALG IM PRO
[6]   Improved morphological top-hat [J].
Jackway, PT .
ELECTRONICS LETTERS, 2000, 36 (14) :1194-1195
[7]  
KOIVISTO P, 1996, IEEE DIG SIGN PROC W
[8]  
KRAFT P, 1995, 5 INT C IEEE IM PROC
[9]  
LI JF, 2003, J CHINA I COMMUNICAT
[10]   Morphological associative memories [J].
Ritter, GX ;
Sussner, P ;
Diaz-de-Leon, JL .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1998, 9 (02) :281-293
12