机构

• 地理科学与资源研究所 [1]
• 长春光学精密机械与物... [1]
• 遥感与数字地球研究所 [1]

采集方式

• OAI收割 [3]

内容类型

• SCI/SSCI论文 [1]
• 会议论文 [1]
• 期刊论文 [1]

发表日期

• 2016 [1]
• 2015 [1]
• 2010 [1]

学科主题

• Remote Sen... [1]

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Improving spring maize yield estimation at field scale by assimilating time-series HJ-1 CCD data into the WOFOST model using a new method with fast algorithms 期刊论文  OAI收割 Remote Sensing, 2016, 卷号: 8, 期号: 4 作者:  Cheng, Zhiqiang;  Meng, Jihua;  Wang, Yiming 收藏  |  浏览/下载：33/0  |  提交时间：2017/04/24 REMOTE-SENSING IMAGES  WAVELET DECOMPOSITION  SPARSE REPRESENTATION  INTENSITY MODULATION  PANCHROMATIC DATA  FUSION TECHNIQUES  SPATIAL DETAILS  QUALITY  ALGORITHMS  TRANSFORM   The effects of constraining variables on parameter optimization in carbon and water flux modeling over different forest ecosystems SCI/SSCI论文  OAI收割 2015 作者:  Liu M.;  He, H. L.;  Ren, X. L.;  Sun, X. M.;  Yu, G. R. 收藏  |  浏览/下载：35/0  |  提交时间：2015/12/09 Eddy covariance  Model data fusion  Parameter optimization  Forest  ecosystems  SIPNET  sensitivity-analysis techniques  net primary production  sub-alpine  forest  terrestrial ecosystems  nonlinear inversion  climate-change  mixed forest  data fusion  co2 fluxes  uncertainty   Restoration of an atmospherically blurred image based on physical model fusion approach (EI CONFERENCE) 会议论文  OAI收割 2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China 作者:  Wang Y.;  Li J.;  Li J.;  Li J.;  Wang Y. 收藏  |  浏览/下载：29/0  |  提交时间：2013/03/25 This paper proposes a new restoration method  only using the single image information  combining atmospheric physical model with fusion techniques to reduce the degradation of the image contrast in bad weather conditions caused by atmospheric aerosols  such as haze and fog. The basic idea of this method is to utilize physics-based model method instead of multisensors to generate a serial of virtual images  and then to fuse those virtual images into a high contrast image based on the wavelet fusion technique. In contrast to previous methods  our restoration technique is not only independent on predicted structure  distributions of scene reflectance  or detailed knowledge about the particular weather condition  but also adapt to the situation without a reference image or images with moving objects captured by a video camera. Experiments on different poorcontrast images demonstrate the availability of the proposed method in case of restoring the atmospherically blurred images. 2010 IEEE.