Optimization Design of Soft Morphological Filters Based on Whole Annealing Genetic Algorithm

ZHAO Chun-hui; SUN Rui; SUN Sheng-he

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Optimization Design of Soft Morphological Filters Based on Whole Annealing Genetic Algorithm

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- Optimization Design of Soft Morphological Filters Based on Whole Annealing Genetic Algorithm
- Acta Electronica Sinica Vol. 30, Issue 1, Pages: 54-57(2002)
- 作者机构：
  
  1. 哈尔滨工程大学电子工程系,黑龙江,哈尔滨,150001
  2. 哈尔滨工业大学自动化测试与控制系,黑龙江,哈尔滨,150001
  3. 哈尔滨工程大学电子工程系黑龙江哈尔滨,150001
  4. 哈尔滨工业大学自动化测试与控制系黑龙江哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.72
- Published：2002
- 稿件说明：
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ZHAO Chun-hui, SUN Rui, SUN Sheng-he. Optimization Design of Soft Morphological Filters Based on Whole Annealing Genetic Algorithm[J]. Acta Electronica Sinica, 2002, 30(1): 54-57.
DOI：

ZHAO Chun-hui, SUN Rui, SUN Sheng-he. Optimization Design of Soft Morphological Filters Based on Whole Annealing Genetic Algorithm[J]. Acta Electronica Sinica, 2002, 30(1): 54-57. DOI：

摘要

整体退火遗传算法(WAGA)是一种新的遗传算法

它将退火机制引入选择算子

并允许父代加入竞争

使遗传算法更加稳健、高效.本文应用WAGA优化柔性形态滤波器

并研究了在不同噪声比例和最小平均绝对误差(MAE)、最小均方误差(MSE)准则下优化算法的性能.仿真实验显示优化后的柔性形态滤波器性能得到较大改善

适于各种噪声图像的滤波.

Abstract

Whole annealing genetic algorithm (WAGA) is a new genetic algorithm.It introduces annealing mechanism to selection operator and allows ancestor to take part in competition

which makes genetic algorithm more robust and efficient.In this paper

we apply WAGA to optimize soft morphological filters and study the performance of optimization algorithm with various noise percentages under MAE or MSE error criteria.The simulation experiments show that optimized soft morphological filters are highly improved and to suit for filtering of noisy images.

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