7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS)最新文献

Edge-aware segmentation in satellite imagery: A case study of shoreline detection 卫星图像中的边缘感知分割:海岸线检测的案例研究

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398319

U. R. Aktas, G. Can, F. Vural

{"title":"Edge-aware segmentation in satellite imagery: A case study of shoreline detection","authors":"U. R. Aktas, G. Can, F. Vural","doi":"10.1109/PPRS.2012.6398319","DOIUrl":"https://doi.org/10.1109/PPRS.2012.6398319","url":null,"abstract":"Shoreline extraction algorithms from multispectral imagery depend on threshold selection over spectral values and segmentation in general. Although this method gives high performance values for water delineation, error is accumulated on pixels near shoreline and complicates detection of nearby ships, docks etc. Water-shadow spectral mixing and spectral difference in water regions are two of the reasons for such untrustworthy shoreline results. With only four bands available, improvement in water detection depending only on pixel values is not very promising. Therefore, segmentation gains importance. By an edge-aware segmentation method, we aim to improve overall water and shoreline detection performances. In this study, a robust three-stage shoreline extraction algorithm is proposed. In the first stage, segmentation is applied over spectral values and then, some segments are combined according to edge information. In the second stage of the algorithm, pixel-based water information is combined with segmentation. The last step consists of enhancement of water regions based on local optimization by merging regions near shore boundary. Additionally, two new boundary-sensitive performance metrics are introduced for measuring the accuracy of the detected boundaries.","PeriodicalId":139043,"journal":{"name":"7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS)","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127287752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Perceptual grouping of row-gestalts in aerial NIR images of urban terrain 城市地形航空近红外图像行格式塔的感知分组

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398321

E. Michaelsen

引用次数: 1

Enhanced recognition using iterative learning fusion in remote sensing images 基于迭代学习融合的遥感图像增强识别

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398322

Qianwen Yang, F. Sun, Huaping Liu

引用次数: 0

Hierarchical band clustering for hyperspectral image analysis 用于高光谱图像分析的分层带聚类

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398316

H. Su, Peijun Du, Q. Du

引用次数: 1

A two-dimensional production system for grouping persistent scatterers in urban high-resolution SAR scenes 城市高分辨率SAR场景中持续散射体的二维生成系统

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398311

L. Schack, A. Schunert, U. Soergel

{"title":"A two-dimensional production system for grouping persistent scatterers in urban high-resolution SAR scenes","authors":"L. Schack, A. Schunert, U. Soergel","doi":"10.1109/PPRS.2012.6398311","DOIUrl":"https://doi.org/10.1109/PPRS.2012.6398311","url":null,"abstract":"Modern spaceborne SAR sensors like TerraSAR-X offer ground resolutions of about one meter in range and azimuth direction which allows for the discrimination between different facade elements. Those objects often feature a trihedral structure, which leads to a strong radar response due to triple-bounce reflection. The resulting radar signal is frequently observed to be temporally stable and usually shows a large amplitude (Persistent Scatterer, PS). Our aim is to aggregate single PS to lattices using Gestalt theory. This is a very important step in the process of unveiling the physical nature of PS since it simplifies the fusion with supplementary data like oblique view aerial images. We use a two stage 2D production system which exploits the knowledge abut mapping of 3D objects into the SAR imaging geometry. In the first step, the production system groups those PS, which are vertically aligned in the real world, to rows. In a second step, those groups are merged to regular lattices with the second orientation corresponding to the horizontal alignment of facade elements. The results show the benefit of aggregating points to lattices by the possible distinction of facade orientations.","PeriodicalId":139043,"journal":{"name":"7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123667226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

3D classification of crossroads from multiple aerial images using conditional random fields 基于条件随机场的多幅航拍图像十字路口三维分类

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398312

S. Kosov, F. Rottensteiner, C. Heipke

引用次数: 1

Global land cover classification using MODIS surface reflectance products 利用MODIS地表反射率产品进行全球土地覆盖分类

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398314

H. Shimoda, K. Fukue

引用次数: 1

Classification of microtopographical features along the shore of Balkhash Lake by ALOS/PRISM DSM Balkhash湖岸微地形特征的ALOS/PRISM DSM分类

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398313

Y. Nakayama, Y. Hara, K. Endo

{"title":"Classification of microtopographical features along the shore of Balkhash Lake by ALOS/PRISM DSM","authors":"Y. Nakayama, Y. Hara, K. Endo","doi":"10.1109/PPRS.2012.6398313","DOIUrl":"https://doi.org/10.1109/PPRS.2012.6398313","url":null,"abstract":"The purpose of this study is to analyze the distribution and the classification of gravel bar along the shore of Balkhash Lake by using the high precision DSM newly produced from the stereo pair data of PRISM carried in ALOS, and to consider the age and environment of formation of every classified gravel bar, and the long-term environmental change based on water level fluctuation of the lake. The classification of gravel bar distribution pattern based on the characteristics such as height, number and direction of the ridge line was carried out through extraction and comparative analysis of the DSM data and ALOS pan-sharpened image in eighteen areas along the shoreline. The result of this study showed that the distribution pattern of the gravel bars along the shore was classified into three typical groups. The difference in distribution of three groups is based on the influence of the waves with the strong prevailing wind. Moreover, according to the feature of the classified group, the water level change situation of Balkhash Lake was divided into three stages in the past about 26,000 years, and the tendency of drawdown was shown as the whole.","PeriodicalId":139043,"journal":{"name":"7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131150649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unsupervised change detection via hierarchical support vector clustering 基于分层支持向量聚类的无监督变化检测

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398309

F. de Morsier, D. Tuia, V. Gass, J. Thiran, M. Borgeaud

引用次数: 7

Despeckling structural loss(DSL): A new metric for measuring structure-preserving capability of despeckling algorithms 消斑结构损失(DSL):一种衡量消斑算法结构保持能力的新指标

7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS) Pub Date : 2012-12-31 DOI: 10.1109/PPRS.2012.6398310

Xuezhi Yang, Li Jia, Yujie Wang, Yiming Tang

引用次数: 0