Suppression of infrared complex background based on adaptive gradient threshold anisotropic filtering

SUN Hai-jiang; WANG Yan-jie; CHEN Xiao-lin

doi:10.3788/OPE.20142201.0146

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Suppression of infrared complex background based on adaptive gradient threshold anisotropic filtering

Information Sciences | 更新时间：2020-08-13

- Suppression of infrared complex background based on adaptive gradient threshold anisotropic filtering
- Optics and Precision Engineering Vol. 22, Issue 1, Pages: 146-151(2014)
- 作者机构：
  
  中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20142201.0146
  CLC： TP391.4
- Received：12 January 2013，
  
  Published：15 January 2014
- 稿件说明：
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孙海江, 王延杰, 陈小林. 基于自适应梯度阈值各向异性滤波抑制红外复杂背景[J]. 光学精密工程, 2014,22(1): 146-151

SUN Hai-jiang, WANG Yan-jie, CHEN Xiao-lin. Suppression of infrared complex background based on adaptive gradient threshold anisotropic filtering[J]. Editorial Office of Optics and Precision Engineering, 2014,22(1): 146-151
孙海江, 王延杰, 陈小林. 基于自适应梯度阈值各向异性滤波抑制红外复杂背景[J]. 光学精密工程, 2014,22(1): 146-151 DOI： 10.3788/OPE.20142201.0146.

SUN Hai-jiang, WANG Yan-jie, CHEN Xiao-lin. Suppression of infrared complex background based on adaptive gradient threshold anisotropic filtering[J]. Editorial Office of Optics and Precision Engineering, 2014,22(1): 146-151 DOI： 10.3788/OPE.20142201.0146.

摘要

在传统各向异性扩散滤波算法的基础上

提出了一种自适应梯度阈值各向异性滤波算法

用于有效地抑制红外复杂背景、滤除噪声

同时增强红外弱小目标。该算法根据图像的局部特性

利用其在不同方向上的梯度特点

判断某点像素是噪声还是图像以及其存在于图像的平滑区域还是边缘区域。文中据此提出了自适应求取边缘函数中的梯度阈值(

值)的方法

解决了原各向异性滤波算法的边缘函数中

值固定单一的问题。实验证明:与原各向异性滤波算法和其他背景抑制算法相比

提出的算法增加了去噪功能

对各种复杂背景抑制效果更好

增强后的图像信噪比提高了近2倍。

Abstract

On the basis of traditional anisotropic diffusion filtering algorithm

an adaptive gradient threshold based anisotropic filtering algorithm is proposed to suppress the infrared complex background

filter out the noise effectively and enhance the infrared dim target. According to the local features of a image and its gradient features in different directions

the algorithm can determine the point of a pixel to be a noise or an image

and can point out the point of the pixel to be in the smooth region or the edge region. Based on above

it proposes a method to calculate the gradient threshold (

value) of the edge function adaptively and to solve the shortcoming that the

value is fixed and single in the edge function of the traditionall anisotropic filtering algorithm. This experiment shows that this algorithm increases the denoising function

suppresses complex background effectively

and enhances Signal to Noise Radio(SNR) of the image by 2 times as compared with that of the original anisotropic filtering algorithm and other background suppression algorithms.

关键词

Keywords

references

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