| 1. | Support vector machine for classification of remotely sensed image
的遥感影像的分类 |
| 2. | Detecting land change automatically from remotely sensed image by templet
模板法自动提取遥感图像耕地变化信息的研究 |
| 3. | Fast multi - level clustering lossless compression algorithm for remotely sensed images
多层次快速聚类的遥感图象无损压缩 |
| 4. | Data partition policy of high - resolution remotely sensed image parallel processing
高分辨率遥感影像并行处理数据分配策略研究 |
| 5. | The extraction of road networks from remotely sensed image is an important part in many scene recognition applications
遥感图像道路网提取是图像识别中的重要问题。 |
| 6. | Remotely sensed images and historical aerial photographs at seven different periods are used to study urban expansion in yixing city , in the taihu lake region , east china in the last 50 years
摘要长期以来，由于历史数据的缺乏，很难获得解放后我国城市扩展的完整过程。 |
| 7. | Multisensor remotely sensed image fusion technique can combine multisensor images and produce a more precise , integrated and reliable estimation and description of them than a single image
多源遥感图像融合技术可以将多源传感器的图像数据进行关联和复合，产生出比单一信息源更精确、更完整、更可靠的估计和判断。 |
| 8. | During the past 20 years , a number of semiautomatic and automatic road detection algorithms in remotely sensed images have been developed . existing methods possess respective merits and drawbacks , without universal adaptability
在过去20年中,涌现出许多半自动和自动道路提取算法,但各种算法都有各自的优缺点,普适性不强。 |
| 9. | At pixel level , on the basis of studying the elementary theories of multisensor data fusion and procedures of pretreatment in remote sensing image fusion , this dissertation summarizes the common methods which are applied in multisensor remotely sensed image fusion
图像融合分为三个层次：像素层、特征层和决策层。本论文的工作是在像素层和特征层展开的，取得了一些有新意的成果。 |
| 10. | And then the paper describes em - mrf iterative algorithm and its realization for the parameter estimation in unsupervised image classiifcation process . the em - mrf - based image classification strategy is introduced into multisensor feature - level image fusion , distributed and centric based fusion methods are proposed . finally , simulated results through sythetic and real remotely sensed image illustrate the effectiveness and advantage of the proposed methods
针对遥感图像非监督分类中的参数估计问题，重点讨论了em - mrf迭代算法的原理和实现，并将em - mrf迭代算法引入到多源遥感图像融合的过程中，提出了两种分别基于集中式融合模型和分布式融合模型的图像融合方法。 |
