机构

• 地理科学与资源研究所 [2]
• 成都山地灾害与环境研... [1]
• 计算技术研究所 [1]
• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [5]

内容类型

• 期刊论文 [4]
• 会议论文 [1]

发表日期

• 2020 [2]
• 2011 [1]
• 2009 [1]
• 2006 [1]

学科主题

筛选

浏览/检索结果: 共5条，第1-5条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 A Partition-Based Detection of Urban Villages Using High-Resolution Remote Sensing Imagery in Guangzhou, China 期刊论文  OAI收割 REMOTE SENSING, 2020, 卷号: 12, 期号: 14, 页码: 19 作者:  Zhao, Lu;  Ren, Hongyan;  Cui, Cheng;  Huang, Yaohuan   |  收藏  |  浏览/下载：6/0  |  提交时间：2021/03/18 urban villages  highly urbanized region  partition strategy  random forest  high-resolution remote sensing images   A Partition-Based Detection of Urban Villages Using High-Resolution Remote Sensing Imagery in Guangzhou, China 期刊论文  OAI收割 REMOTE SENSING, 2020, 卷号: 12, 期号: 14, 页码: 19 作者:  Zhao, Lu;  Ren, Hongyan;  Cui, Cheng;  Huang, Yaohuan   |  收藏  |  浏览/下载：17/0  |  提交时间：2021/03/18 urban villages  highly urbanized region  partition strategy  random forest  high-resolution remote sensing images   Research on water resources conservation of mountain river based on the concept of region partition 期刊论文  OAI收割 JOURNAL OF MOUNTAIN SCIENCE, 2011, 卷号: 8, 期号: 4, 页码: 582–591 Liu Yubang; Tao Qingyu; Liang Chuan; Wu Yong 收藏  |  浏览/下载：28/0  |  提交时间：2013/08/12 Water resources conservation  Mountain river  Region partition  Mountain ecosystems   A fast adaptive load balancing method for parallel particle-based simulations 期刊论文  OAI收割 SIMULATION MODELLING PRACTICE AND THEORY, 2009, 卷号: 17, 期号: 6, 页码: 1032-1042 作者:  Zhang, Dongliang;  Jiang, Changjun;  Li, Shu   |  收藏  |  浏览/下载：16/0  |  提交时间：2019/12/16 Region partition  Adaptive load balancing  Parallel particle-based simulation   A new segmentation method of CR images based on discrete wavelet transform and mathematics morphology (EI CONFERENCE) 会议论文  OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者:  Li Z.;  Li Z. 收藏  |  浏览/下载：68/0  |  提交时间：2013/03/25 In this paper  we propose a segmentation method of CR(computed radiography) images with being rid of under-segmentation and over-segmentation. An under-segmentation occurs when pixels belonging to different objects are grouped into a single region. Such errors are the most dangerous because they can invalidate the whole segmentation process. The phenomenon always takes place when we segment CR images because of the principle of CR. In order to depressed under-segmentation  we enhance the CR images using DWT (discrete wavelet transform) to get more detail of CR image features. As we enhance the CR image  the over-segmentation maybe occurs. Compared with under-segmentation  the over-segmentation occurs when a single objects is subdivided by segmentation into several region. For the purpose of preventing from the over-segmentation  we present a scheme for enhanced CR images based on watershed algorithm that solves over-segmentation problem. We use marker-based watershed algorithm. Together with gradient image and marker image  watershed segmentation can make sure to partition CR image into meaningful object and avoid further segmentation of homogeneous regions. The result of the proposed algorithm are compared with those of other standard methods. Experiments have shown a better result and indeed solved under-segmentation and over-segmentation problems.