Earticle

초록

영어

Hyperspectral Image processing is usually time consuming, due to its huge data size. Nowadays Hyperspectral Imaging is used in many fields where real-time solutions are required. A systemic comparison study of linear feature extraction methods for classification of hyperspectral images with various types of noises is carried out in this paper, in which the performance of different linear feature extraction methods for classification and their computation cost reduction are compared. In practice, hyperspectral images are often contaminated by different types of noises, as the atmosphere around hyperspectral cameras may change all the time. In this paper, to make it more realistic, different types of noises, including Salt-and-Pepper noise, Gaussian noise, Speckle noise and their mixtures, are artificially imposed on the hyperspectral image. Support Vector Machine based classification is employed for classification performance comparison. The experimental results are very helpful for selecting linear feature extraction methods for classification of hyperspectral images that are usually affected with noises.

목차

Abstract
 1. Introduction
 2. Selected Linear Feature Extraction Methods
 3. Image Noises
  3.1. Salt-and-Pepper Noise
  3.2. Gaussian Noise
  3.3. Speckle Noise
 4. Experimental Results
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Farid Muhammad Imran [ Shaanxi Key Laboratory of Information Acquisition and Processing, Center for Earth Observation, School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710129, China ]
• Mingyi He [ Shaanxi Key Laboratory of Information Acquisition and Processing, Center for Earth Observation, School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710129, China ]
• Yifan Zhang [ Shaanxi Key Laboratory of Information Acquisition and Processing, Center for Earth Observation, School of Electronics and Information, Northwestern Polytechnical University, Xi’an, 710129, 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