Earticle

초록

영어

Through the research of the application of support vector machine theory in the pixel unmixing, the advantages of the weighted posterior probability support vector machine theory in pixel unmixing is presented. Considering the difference of each support vector machine classifier, posterior probability pixel is used as weight coefficient of sub-pixel classification for pixels unmixing. This paper presents a weighted posterior probability support vector machine mixed pixel unmixing method. This method not only has the nonlinear model decomposition characteristics of high precision, but also reduces the standard support vector machine calculating the amount of multi classifier, and it has strong adaptability.

목차

Abstract
 1. Introduction
 2. The Principle of Support Vector machine
 3. Application of Support Vector Machine in the Processing of Remote Sensing Image
 4. Support Vector Machine based on Weighted Posteriori Probability
  4.1. Support Vector Machine based on Weighted Posteriori Probability
  4.2. Method for Determining the Weighted Posterior Probability of Sample Points
 5. Experimental Analysis and Results
  5.1. Experimental Data
  5.2. Accuracy Evaluation
 6. Conclusion
 Acknowledgement
 References

키워드

저자

• Yunfeng Liu [ College of Earth Sciences, Jilin University, Jinlin 130021, china ]
• Laijun Lu [ College of Earth Sciences, Jilin University, Jinlin 130021, 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