计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (34): 190-192.

• 图形、图像、模式识别 • 上一篇    下一篇

形态学高帽变换与低帽变换功能扩展及应用

朱士虎   

  1. 徐州师范大学 物理与电子工程学院,江苏 徐州 221116
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-12-01 发布日期:2011-12-01

Function extension and application of morphological top-hat transformation and bottom-hat transformation

ZHU Shihu   

  1. School of Physics & Electronic Engineering,Xuzhou Normal University,Xuzhou,Jiangsu 221116,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-12-01 Published:2011-12-01

摘要: 数学形态学广泛应用于图像处理和模式识别领域。对形态学高帽变换与低帽变换功能进行扩展,提出了假高帽变换的概念和低帽变换的新方法。用形态学滤波对原始图像进行平滑处理,由形态学膨胀运算调整结构元素尺度,依据检测图像边缘熵确定权值进行融合。改进了传统形态学边缘检测算法,改善了亮背景上暗物体的边缘提取,对数字图像进行处理,满足了实际需求。实验结果表明,该算法能有效抑制噪声,且边缘清晰准确,效果优于经典的边缘检测算法。

关键词: 形态学, 边缘检测, 功能扩展, 信息熵, 图像融合

Abstract: Mathematical morphology is widely applied in image processing and pattern recognition.This paper proposes pseudo top-hat transformation and new bottom-hat transformation.The original image is filtered using open-and-close operation.The scale of structure elements can be determined by dilation operation.A new edge image with a better quality fused by their entropy can effectively be extracted using proposed ways.Experimental results indicate that the algorithm can effectively suppress noise and improve dim edge detection;the edges are clear and accurate.So the new edge detection method achieves better image processing effect than classical edge detection methods.

Key words: morphology, edge detection, function extension, information entropy, image fusion