期刊文献+

一种适用于SAR图像的2维Otsu改进算法 被引量:12

Improved 2D Otsu Algorithm for SAR Images
下载PDF
导出
摘要 Otsu法是图像阈值分割中的经典算法之一,在图像处理中得到广泛的应用。针对原始2维Otsu法直方图区域划分上的缺陷和运算速度慢的缺点,分析了适用于SAR图像相干斑乘性噪声的直方图区域划分方法,提出了一种更符合实际图像模型的阈值选取准则。实验结果表明,该改进算法的分割效果良好,运算速度也有很大提高。 As one of the classic threshold methods for image segmentation, Otsu algorithm has been widely applied in image processing. Based on the analysis of the original 2D Otsu which has the disadvantages such as histogram area partition and time consuming, this paper introduces a new method of area partition in terms of speckle noise in SAR images, and brings forward a new rule of threshold selection which fits the image model better. The experiments show that the segmentation effect of the improved algorithm is better and its computational speed has been greatly improved.
出处 《中国图象图形学报》 CSCD 北大核心 2009年第1期14-18,共5页 Journal of Image and Graphics
基金 武器装备预研重点基金项目(9140A03010407KG0113)
关键词 阈值分割 Otsu法2维直方图 最大类间方差 合成孔径雷达(SAR) threshold segmentation, Otsu algorithm, 2D histogram, maximum between-class variance, SAR
  • 相关文献

参考文献10

二级参考文献45

  • 1李立源,陈维南.一种强鲁棒的完全确定型的快速阈值化方法[J].模式识别与人工智能,1993,6(3):235-241. 被引量:13
  • 2刘健庄,栗文青.灰度图象的二维Otsu自动阈值分割法[J].自动化学报,1993,19(1):101-105. 被引量:355
  • 3[1]Pal N R,Pal S K.A Review on Image Segmentation Techniques[J].Pattern Recognition,1993,26(9):1277-1294.
  • 4[2]Bhanu B,Lee S,Ming J.Alaptive Image Segmentation Using a Genetic Algorithm[J].IEEE Trans.on System,Man,and Cybernetics,1995,5(12):1543-1565.
  • 5[3]Doyle W.Operation Useful for Similarity-Invariant Pattern Recognition[J].J.Asssoc.Comput.Mach.,1962,9:259-267.
  • 6[4]Lee S,Chung S.A Comparative Performance Study of Several Global Thresholding Techniques for Segmentation[J].Computer Vision,Graphics,and Image Processing,1990,52:171-190.
  • 7[5]Ostu N A.Threshold Selection Method from Gray-Level Histograms[J].IEEE Trans.on System,Man,and Cybernetics,1979,9(1):62-66.
  • 8[6]Tsai W H.Moment-Preserving Thresholding:A New Approach[J].Computer Vision,Graphics,and Image Processing,1985,29:377-393.
  • 9[7]Kittler J,Illingworth J.Minimum Error Thresholding[J].Pattern Recognition,1986,19:41-47.
  • 10[8]Cho S,Haralick R,Yi S.Improvement of Kittler and Illingworth's Minimum Error Thresholding[J].Pattern Recognition,1989,22:609-617.

共引文献831

同被引文献114

引证文献12

二级引证文献139

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部