Earticle

초록

영어

In recent years, the theory of partial differential equations (PDE) for its rigorous mathematical theory foundation has been widely used in the fields of image processing. Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease. In order to detect the noise in the medical images, many models are studied, but the noises in medical images are much more complex than typical images. This paper introduces a new image noise detection approach using morphology and partial differential equations where are based on the morphology reconstruction with anisotropic diffusion to make full use of the advantage of Catte model. This proposed approach has been tested with the biomedical cell images with comparing with the Catte model, PM model and Canny model. The experimental results show that this proposed approach outperforms the other three models in terms of defined indicator and efficiency.

목차

Abstract
 1. Introduction
 2. Basic Catte Model
 3. New Model for Noise Detection based on Morphology and Partial Differential Equations
  3.1 Morphology Re-construction
  3.2 New Partial Diffusion Equations
  3.3 Parameter Setting
 4. Experimental Results and Discussions
 5. Conclusion
 References

키워드

저자

• Yubin Li [ Gannan Normal University, Ganzhou, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605