Earticle

초록

영어

In this paper, we propose a novel game theory based framework for synthetic aperture radar image de-noising and segmentation based change detection. We find out the balance of the two aspects. The Nash game theory helps us find out the balance of segmentation accuracy and overall de-noising performance. In the de-noising part, we adopt the multi-diagonal matrix filter based algorithm to undertake the de-noising mission. Segmentation and change detection are finalized by the state-of-the-art methodologies in which the segmentation procedure transfers the difference map into the change map. As far as time-consuming is concerned, we compare the different methods for generating difference map. Fusion map is selected to be our difference map for image segmentation using fuzzy clustering. The experimental analysis shows the effectiveness and robustness of our propose framework with the comparison of other well-known change detection algorithms under the outer environment of noisy and noise-free. Finally, some potential optimization methods are discussed for future research.

목차

Abstract
 1. Introduction
 2. The Segmentation and De-noising
  2.1. The Image Segmentation
  2.2. The Image De-noising with Multi-diagonal Matrix Filter
 3. Balance Segmentation and De-noising using Game Theory
  3.1. The Theoretical Analysis
  3.2. The General Steps of Proposed Method
 4. Comparison of Three Difference Maps
  4.1. The Minus Map
  4.2. The Ratio Map
  4.3. The Fusion Map
 5. Experiment and Analysis
 6. Conclusion and Summary
 References

키워드

저자

• Bingquan Huo [ Binzhou Polytechnic, Shandong, China ]
• Fengling Yin [ Binzhou Polytechnic, Shandong, 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