计算机工程 ›› 2009, Vol. 35 ›› Issue (23): 212-213,.doi: 10.3969/j.issn.1000-3428.2009.23.073

• 图形图像处理 • 上一篇    下一篇

基于轮廓结构元素和阈值分割的形态学去噪

胡学刚,吴 勇   

  1. (重庆邮电大学计算机科学与技术学院,重庆 400065)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-12-05 发布日期:2009-12-05

Morphology Denoising Based on Contour Structure Elements and Threshold Segmentation

HU Xue-gang, WU Yong   

  1. (College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-12-05 Published:2009-12-05

摘要: 将图像分割技术应用于图像复原,提出基于轮廓结构元素和阈值分割的数学形态学去噪算法。该算法对图像进行阈值分割得到目标图像和背景图像,采用不同的轮廓结构元素滤波器算子对得到的2幅图像进行滤波并合成。实验结果表明,与其他形态学滤波算法相比,该算法有效地抑制了噪声,对主要目标的边缘细节起到了较好的保护作用。

关键词: 图像去噪, 轮廓结构元素, 阈值分割, 数学形态学

Abstract: Image segmentation technology is applied to image restoration, and the solution to morphologic noise reduction based on contour structure elements and threshold segmentation is proposed. This algorithm gains object and background image by threshold segmentation, uses two different contour structure elements filters to filter noises for object and background image differently, and merges object and background as a final image. Experimental result demonstrates that compared with other filters of morphological algorithm, the algorithm has a better control over noises, and plays a more effective role in the protection of the main objects’ edge details.

Key words: image denoising, contour structure elements, threshold segmentation, mathematical morphology

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