|
|||||
|
|
| 基于显著性图像与纹理特征的遥感影像云检测 | |
| 引用本文： | 黄宇,潘励. 基于显著性图像与纹理特征的遥感影像云检测[J]. 测绘地理信息, 2021, 46(2): 16-19. DOI: 10.14188/j.2095-6045.2019040 |
| 作者姓名： | 黄宇 潘励 |
| 作者单位： | 武汉大学遥感信息工程学院 ,湖北 武汉 ,430079 |
| 基金项目： | 国家自然科学基金(41771363)。 |
| 摘 要： | 遥感影像云检测是遥感影像处理中非常关键的环节,准确识别影像含云区域能够提升影像的利用价值.根据遥感影像的成像特点,将阈值法和纹理特征结合实现云和下垫面的分割.首先将影像从RGB(red-green-blue)空间转化为HSI(hue-saturation-intensity)空间,进而构建影像的显著性图像,利用Otsu... |
| 关 键 词： | 云检测 显著性图像 灰度共生矩阵 |
Cloud Detection of Remote Sensing Images Based on Significance Maps and Texture Features |
|
| HUANG Yu,PAN Li. Cloud Detection of Remote Sensing Images Based on Significance Maps and Texture Features[J]. Journal of Geomatics, 2021, 46(2): 16-19. DOI: 10.14188/j.2095-6045.2019040 | |
| Authors: | HUANG Yu PAN Li |
| Affiliation: | (School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China) |
| Abstract: | Cloud detection of remote sensing image is a key point in remote sensing image processing,accurate identification of cloud areas can improve the value of image utilization.According to the imaging characteristics of remote sensing images,this paper combines threshold method and texture features to realize the segmentation of cloud and underlying surface.Firstly,the image is transformed from RGB space to HSI space,and then the saliency image is constructed.Secondly the saliency image is roughly segmented by Otsu method.Then,the texture features of cloud and underlying surface are analyzed based on gray level co-occurrence matrix,and the accurate cloud area is further extracted.Experiments show that the algorithm has low complexity and fine extraction effect. |
| Keywords: | cloud detection saliency image gray level co-occurrence matrix |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |