Application of efficient image segmentation method based on local fractal in the infrared cloud image processing

LIU Yang; TIAN XIAO-jian; WANG Qing; GAO Bo

doi:10.3788/OPE.20111906.1367

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Application of efficient image segmentation method based on local fractal in the infrared cloud image processing

Article | 更新时间：2020-08-12

- Application of efficient image segmentation method based on local fractal in the infrared cloud image processing
- Optics and Precision Engineering Vol. 19, Issue 6, Pages: 1367-1374(2011)
- 作者机构：
  
  1. 吉林大学通信工程学院,吉林长春,130022
  2. 吉林大学电子科学与工程学院,吉林长春,130012
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111906.1367
  CLC： TP391.41
- Received：30 April 2010，
  
  Revised：04 November 2010，
  
  Published Online：25 June 2011，
  
  Published：25 June 2011
- 稿件说明：
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刘洋, 田小建, 王晴, 高博. 采用局部分形的高效图像分割方法在红外云图处理中的应用[J]. 光学精密工程, 2011,19(6): 1367-1374

LIU Yang, TIAN Xiao-jian, WANG Qing, GAO Bo. Application of efficient image segmentation method based on local fractal in the infrared cloud image processing[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1367-1374
刘洋, 田小建, 王晴, 高博. 采用局部分形的高效图像分割方法在红外云图处理中的应用[J]. 光学精密工程, 2011,19(6): 1367-1374 DOI： 10.3788/OPE.20111906.1367.

LIU Yang, TIAN Xiao-jian, WANG Qing, GAO Bo. Application of efficient image segmentation method based on local fractal in the infrared cloud image processing[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1367-1374 DOI： 10.3788/OPE.20111906.1367.

摘要

针对已有的基于分形维数的图像分割算法难以快速计算一个小区域的分形维数

计算复杂

效率低的问题

通过分析云的分形特征

提出一种采用局部分形维数的方法对红外云彩图像进行分割。首先

提出了一种高效算法来计算一段区间内的分形维数

使用树状数组作为数据结构

利用已经计算出来的信息

在

(log

)的时间内得到结果;然后

通过计算云图每个水平线的分形维数

将分形维数超过一定阈值的区域确定为云彩区域;最后

将每条水平线的高维数区间结合在一起得出整个分割结果。实验结果表明

该方法解决了传统的分形维数算法在大量计算维数时算法复杂度高、计算时间长的问题

对于640 pixel480 pixel的大型图像计算时间

0.1 s;同时该算法能够有效地将云彩和其他人工遮挡物以及背景光线变化和局部噪声区分开

取得满意的处理效果。

Abstract

An efficient image segmentation method based on local fractal dimension was proposed by analyzing the fractal characteristics of clouds to solve the problems existed in image segmentation algorithms in high complexity

low efficiency and difficult to calculate the fractal dimension of a small area quickly. Firstly

an efficient algorithm to calculate the fractal dimension of a small area was proposed. By utilizing a tree array as data structure and taking the advantage of calculated information

the result could be obtained in the time of

(log

). Then

through calculating the fractal dimension of each horizontal line in the infrared cloud image

the fractal dimension that exceeds a certain threshold area was identified as the cloud area. Finally

the segmentation result was gotten through combining all the high dimensions of each horizontal line. The result demonstrates that this method solves the problems of complexity and inefficiency of the traditional methods based on fractal dimension

and the computing time remains less than 0.1 s for a large image of 640 pixel480 pixel. The algorithm can effectively separate the clouds from the other artificial objects

changed background light

and the local noise to obtain good segmentation results.

关键词

Keywords

references

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