원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vol.8 No.3
2015.03
pp.325-336
피인용수 : 0건 (자료제공 : 네이버학술정보)
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보