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  1. (1.西北工业大学 国防科学研究院,陕西 西安 710072; 2. 西安电子科技大学 经济管理学院,陕西 西安 710071; 3. 深圳大学 信息工程学院,广东 深圳 518060)

  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2005-04-20 发布日期:2005-04-20

A novel adaptive image fuzzy enhancement algorithm

WANG Bao-ping1;LIU Huai-liang2;LI Nan-jing1;XIE Wei-xin3


  1. (1. Northwest Polytechic University, Defence Science and Technology Academe, Xi′an 710072, China; 2. School of Economic Management, Xidian Univ., Xi′an 710071, China; 3. Inst. of Information Engineering, Shenzhen Univ., Shenzhen 518060, China)
  • Received:1900-01-01 Revised:1900-01-01 Online:2005-04-20 Published:2005-04-20

摘要: 对图像模糊增强算法中的非线性变换进行了研究,发现了其存在变换强度较小,运算速度较慢,丢失部分灰度信息等缺点.提出了一种新的模糊增强变换算子,该变换算子不但克服了上述缺点,而且具有封闭性、变换强度可调以及移植性好等优点.另外,针对以往算法选取阈值参数的随机性问题,通过引入模糊熵,使阈值的选取具有了一定的目的性.将新的模糊增强算法应用于图像边缘检测中,取得了优于现有模糊增强方法的效果.

关键词: 图像增强, 边缘检测, 隶属度函数

Abstract: The no-linearity transform in image enhancement is studied in detail, and its drawbacks are found, on the basis of which a novel image fuzzy enhancement arithmetic operator is proposed, which not only has a closing character and an automatic-adjusting character, but also has a transplant character to other enhancement arithmetic. In addition, by quoting fuzzy entropy, the selection of the threshold value in image enhancement is beneficial to a certain extent. We use our new algorithm to extract image edges, with a better result than that of the now-available image fuzzy enhancement method.

Key words: image enhancement, edge detection, membership function


  • TP391.41