期刊文献+

自适应模糊边缘减宽增强算法 被引量:3

An Adaptive Algorithm of Fuzzy Edge Width Reduction
下载PDF
导出
摘要 针对形态边缘减宽增强算法的不足,提出了一种自适应模糊边缘减宽增强算法。它对非边缘区采用局部均值滤波来抑制噪声;对于边缘区域,根据梯度方向及当前点在斜坡边缘的位置,自适应的采用边缘方向均值、边缘梯度方向的高灰度均值和低灰度均值来代替当前像素灰度值,从而缩短斜坡边缘的宽度来达到增强图像边缘的目的。采用模糊策略决策,推理合成得到增强结果,在增强的同时,抑制噪声。实验结果表明,该算法能有效地增强边缘并平滑噪声,明显地改善视觉效果。 The shortcoming of morphological edge enhancement algorithm has been discussed. Based on that, an adaptive edge width reduction enhancement fuzzy algorithm is presented. It uses local gray mean filter to smooth noise in the non-edge areas. In edge areas, it adaptively uses the gray means of edge direction, the means of high gray and low gray in gradient direction to replace the current pixel gray to reach the purpose of reducing ramp edge width. Membership functions are introduced to describe the degree of whether the dot is in the edge area or in the homogeneous area. Fuzzy strategy has been used to control the enhancement. Results of experiments show that this method enhances the ramp edges while reducing the noise.
出处 《中国图象图形学报》 CSCD 北大核心 2009年第2期255-259,共5页 Journal of Image and Graphics
基金 武器装备预研基金项目(NO9140A21040306KG0195)
关键词 模糊 边缘减宽 斜坡边缘 边缘增强 fuzzy, edge width reduction, ramp edge, edge, enhancement
  • 相关文献

参考文献6

  • 1Pal S K, King R A. Image enhancement using smoothing with fuzzy sets [ J ]. IEEE Transactions on Systems, Man and Cybernetics, 1981, 11(7) : 494-501.
  • 2王晖,张基宏.图像边界检测的区域对比度模糊增强算法[J].电子学报,2000,28(1):45-47. 被引量:48
  • 3Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion [ J ]. IEEE Transactions on PAMI, 1990, 12 ( 7 ) : 629-639.
  • 4Leu J G. Edge sharpening through ramp width reduction [ J ]. Image and Vision Computing, 2000, 18(6-7):501-514.
  • 5Sehavemaker J, Reinders M, Gerbrands J, et al. Image sharpening by morphological filtering [ J ]. Pattern Recognition, 2000, 33 ( 6 ) : 997-1012.
  • 6冯国进,顾国华,陈钱.基于形态学的红外图像边缘增强[J].激光与红外,2003,33(6):453-454. 被引量:9

二级参考文献5

共引文献55

同被引文献30

  • 1李少达,杨佳,刘汉湖,杨容浩.一种改进的自适应模糊图像增强方法[J].中国图象图形学报,2007,12(8):1339-1343. 被引量:5
  • 2RUSSO F.An image enhancement technique combining sharpening and noise reduction[J].IEEE Transactions on Instrumentation and Measurement,2002,51 (4):824 -828.
  • 3CHAN T,ESEDOGLU S,PARK F,et al.Total variation image restoration:Overview and recent developments[Z].Handbook of Mathematical Models in Computer Vision.2006:17-31.
  • 4AUBERTG,AUJOL.J F.A variational approach to remove multiplicative noise[J].SIAM Journal on Applied Mathematics,2008,68(4):925-946.
  • 5STARCK J L,CANDES E J.The curvelet transform for image denoising[J].IEEE Trans Image Proc,2002,11 (6):670-684.
  • 6CHENG H D,CHEN Y H.Fuzzy partition of two-dimensional histogram and its application to thresholding[J].Pattern Recognition Society,1999,32(5):825-843.
  • 7PANKANTI S,PRABHAKAR S,JAIN A K.On the individuality of fingerprints[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(8):1010-1025.
  • 8WANG S,ZHANG W W,WANG Y S.Fingerprint classification by directional fields[C] // Proceedings of the 4th IEEE International Conference on Muhimodal Interfaces Pittsburgh.Pennsylvania,USA,2002:395-399.
  • 9MOHAMMEDS,FIAIDHI J,YANG L.Morphological analysis of mammograms using visualization pipelines[J].Pakistan Journal of Information and Technology,2003,2 (2):178-190.
  • 10WHARTON E,AGAIAN S,PANETTA K.A logarithmic measure of image enhancement[C] //Proceedings of SPIE:The International Society for Optical Engineering.2006,6250:62500P.

引证文献3

二级引证文献5

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