Earticle

초록

영어

The pre-processed remote sensing images are often polluted by Gaussian and salt-pepper noises. In order to solve this problem, a Sobel-TV based hybrid model is proposed to de-noise the pre-processed remote sensing images. It uses TV model to de-noise and uses Sobel algorithm to control smoothness of the image’ edge. This proposed method will not only efficiently remove image noise but also simultaneously reserves detail information such as edge and texture. Experimental results show the proposed algorithm achieves better SNR and SSIM compared with other methods. In terms of visual quality, the proposed algorithm can remove the noise of the images and preserve more details, which is important value to preprocess remote sensing image.

목차

Abstract
 1. Introduction
 2. Literature Review
  2.1. Gaussian Filter
  2.2. Mean Filter
  2.3. Median Filter
  2.4. Wiener Filter
 3. Methodology
 4. Algorithm Implementation
 5. Numerical Experiments
  5.1. Parameter Values [19-21]
  5.2. Experiments on Simulated Noisy Images
 6. Conclusion
 References

키워드

저자

• TU Jihui [ Electronics & Information School of Yangtze University, Jingzhou, Hubei 434023, China ]
• Zheng Jiang [ Powerchina kunming engineering corporation CO., LTD, Kunming, Yunnan 650051, China ]
• Wu Xiaodong [ Powerchina kunming engineering corporation CO., LTD, Kunming, Yunnan 650051, 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