中国科学院机构知识库网格系统: 检索

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	A novel Greenness and Water Content Composite Index (GWCCI) for soybean mapping from single remotely sensed multispectral images 期刊论文 OAI收割 REMOTE SENSING OF ENVIRONMENT, 2023, 卷号: 295, 页码: 16 作者: Chen, Hui; Li, Huapeng; Liu, Zhao \| 收藏 \| 浏览/下载：41/0 \| 提交时间：2023/10/09 Soybean mapping methods Automatic crop mapping Sentinel-2 Short-wave infrared (SWIR) Normalized difference vegetation index (NDVI)
	帕米尔山区结构和岩性的遥感制图方法研究学位论文 OAI收割北京: 中国科学院大学, 2019 作者: JAVHAR AMINOV \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2021/12/10 遥感岩性测绘图像增强图像处理自动线性提取 Landsat OLI Sentinel-1 Sentinel 2 SE 帕米尔地质学 Remote sensing Lithological mapping Image enhancement Image processing automatic lineament extraction Landsat-8 Sentinel-1 Sentinel-2 SE Pamir Geology
	A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China 期刊论文 OAI收割 REMOTE SENSING, 2018, 卷号: 10, 期号: 12, 页码: 16 作者: Hu, Yunfeng; Zhang, Qianli; Zhang, Yunzhi; Yan, Huimin \| 收藏 \| 浏览/下载：56/0 \| 提交时间：2019/05/23 land cover/land use image classification automatic mapping accuracy evaluation methods comparison Landsat OLI imagery
	A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China 期刊论文 OAI收割 REMOTE SENSING, 2018, 卷号: 10, 期号: 12, 页码: 16 作者: Hu, Yunfeng; Zhang, Qianli; Zhang, Yunzhi; Yan, Huimin \| 收藏 \| 浏览/下载：25/0 \| 提交时间：2019/05/23 land cover/land use image classification automatic mapping accuracy evaluation methods comparison Landsat OLI imagery
	A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China 期刊论文 OAI收割 REMOTE SENSING, 2018, 卷号: 10, 期号: 12, 页码: 16 作者: Hu, Yunfeng; Zhang, Qianli; Zhang, Yunzhi; Yan, Huimin \| 收藏 \| 浏览/下载：18/0 \| 提交时间：2019/05/23 land cover/land use image classification automatic mapping accuracy evaluation methods comparison Landsat OLI imagery
	A new gradient shimming method based on undistorted field map of B-0 inhomogeneity 期刊论文 OAI收割 JOURNAL OF MAGNETIC RESONANCE, 2016, 卷号: 265, 页码: 25-32 作者: Bao, Qingjia; Chen, Fang; Chen, Li; Song, Kan; Liu, Zao 收藏 \| 浏览/下载：30/0 \| 提交时间：2016/07/12 NMR spectrometer Automatic shimming Gradient shimming High resolution spectra B-0 inhomogeneity Field mapping
	A new gradient shimming method based on undistorted field map of B-0 inhomogeneity 期刊论文 OAI收割 JOURNAL OF MAGNETIC RESONANCE, 2016, 卷号: 265, 页码: 25-32 作者: Bao, Qingjia; Chen, Fang; Chen, Li; Song, Kan; Liu, Zao 收藏 \| 浏览/下载：17/0 \| 提交时间：2016/07/12 NMR spectrometer Automatic shimming Gradient shimming High resolution spectra B-0 inhomogeneity Field mapping
	A line mapping based automatic registration algorithm of infrared and visible images 会议论文 OAI收割 5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013 作者: Ai R(艾锐); Shi ZL(史泽林); Xu DJ(徐德江); Zhang CS(张程硕) 收藏 \| 浏览/下载：35/0 \| 提交时间：2013/12/26 There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.