J4 ›› 2014, Vol. 41 ›› Issue (6): 195-198.doi: 10.3969/j.issn.1001-2400.2014.06.032

• 研究论文 • 上一篇    



  1. (长安大学 信息工程学院,陕西 西安  710064)
  • 收稿日期:2013-09-04 出版日期:2014-12-20 发布日期:2015-01-19
  • 通讯作者: 崔华
  • 作者简介:崔华(1977-),女,副教授,博士,Email: huacui@chd.edu.cn.
  • 基金资助:


Image enhancement using the improved partial differential equation

CUI Hua;ZHOU Tingjie;GUO Lu;YUAN Chao;SONG Huansheng   

  1.  (School of Information Engineering, Chang'an University, Xi'an  710064, China)
  • Received:2013-09-04 Online:2014-12-20 Published:2015-01-19
  • Contact: CUI Hua



关键词: 图像增强, 偏微分方程, P-M模型, 相干增强扩散, 路面图像


Excellent preprocessing is necessary for the crack extraction from pavement images. This paper adopts the Partial Differential Equation method to do that, and then improves the P-M diffusion coefficient and fuses it with coherence enhancing diffusion, thus forming the new PDE model. The new PDE model makes the improved P-M diffusion dominates the region without crack edges and coherence enhancing diffusion close to the crack edges, thereby realizing the crack image denoising and enhancing in a more effective way. Theoretical analysis and simulation results consistently show that the proposed model outperforms the classical P-M model in terms of pavement image denoising and enhancing. Furthermore, after the pavement images are preprocessed by the proposed PDE model, cracks are detected more accurately, demonstrating the superiority of the proposed preprocessing method.

Key words: image enhancement, partial differential equation, P-M model, coherence enhancing diffusion, pavement images


  • TP391.41