| 基于NSCT和改进模糊的遥感图像增强方法 |
| |
| 引用本文： | 周 飞,贾振红,杨 杰,Nikola Kasabov.基于NSCT和改进模糊的遥感图像增强方法[J].计算机工程与应用,2017,53(15):206-209. |
| |
| 作者姓名： | 周 飞 贾振红 杨 杰 Nikola Kasabov |
| |
| 作者单位： | 1.新疆大学 信息科学与工程学院，乌鲁木齐 830046
2.上海交通大学 图像处理与模式识别研究所，上海 200240
3.新西兰奥克兰理工大学 知识工程与发现研究所，新西兰 奥克兰 1020 |
| |
| 摘 要： | 为了解决遥感图像处理过程中噪声放大和图像失真现象，提出了一种结合NSCT和改进模糊对比度的图像增强方法。通过NSCT变换把图像分解成低频子带和若干个高频子带；对低频子带进行线性增强，并利用改进的阈值函数对高频子带进行去噪；随后采用改进的模糊对比度来调整NSCT反变换的系数，以提高图像的整体对比度。实验结果表明，提出的算法的客观指标明显优于其他对比算法，并且视觉效果也得到很大改善。
|
| 关 键 词： | 遥感图像 图像增强 NSCT变换 线性变换 自适应阈值 模糊对比度 |
Enhancement method of remote sensing image based on NSCT and improved fuzzy contrast |
| |
| ZHOU Fei,JIA Zhenhong,YANG Jie,Nikola Kasabov.Enhancement method of remote sensing image based on NSCT and improved fuzzy contrast[J].Computer Engineering and Applications,2017,53(15):206-209. |
| |
| Authors: | ZHOU Fei JIA Zhenhong YANG Jie Nikola Kasabov |
| |
| Affiliation: | 1.College of Information Science and Engineering，Xinjiang University, Urumqi 830046, China
2.Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China
3.Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland 1020, New Zealand |
| |
| Abstract: | In order to solve the phenomenon of amplifying noise and image distortion in the process of remote sensing image, an enhancement method is proposed based on NSCT and improved fuzzy contrast. The original image is decomposed into the NSCT domain with a low-frequency sub-band and several high-frequency sub-bands. Linear transformation is adopted for the coefficients of the low-frequency sub-bands. An adaptive threshold method is used for the removal of high-frequency image noise. Subsequently, the improved fuzzy set is used to enhance the global contrast modifying the inverse coefficient of NSCT. Experimental results show that the proposed method not only is superior to other comparative methods in objective criterions, but also can get better visual effect. |
| |
| Keywords: | remote sensing image image enhancement NSCT linear transformation adaptive threshold fuzzy contrast |
|
| 点击此处可从《计算机工程与应用》浏览原始摘要信息 |
|
点击此处可从《计算机工程与应用》下载全文 |
