3D terrain visualization of geographic information systems(GIS)data has become an important issue in recent years.This is due to the emergence of new geo-browsers such as Google Earth,widely popular among users.The av...3D terrain visualization of geographic information systems(GIS)data has become an important issue in recent years.This is due to the emergence of new geo-browsers such as Google Earth,widely popular among users.The availability of 3D representation tools has increased the demand for 3D terrain visualization.The aim of this paper is to review the literature related to the 3D terrain visualization of GIS data from the first map produced until the online mapping era.The reviews are divided into four different sections:manual visualization of 3D terrain,automated visualization of 3D terrain,online visualization of 3D terrain,and software for visualizing 3D terrain.Then,the paper compares between the different types of systems developed by various authors based on the capabilities and the limitations of the system.Some of the techniques have their own strengths and limitations which solve the problem in 3D terrain visualization.However,the research on improving 3D terrain visualization is still ongoing.This is due to the popularity of online environments and mobile devices that render 3D terrain.This review paper will help interested users understand the current state of 3D terrain visualization of GIS data in a better way.展开更多
A fast image segmentation algorithm based on salient features model and spatial-frequency domain adaptive kernel is proposed to solve the accurate discriminate objects problem of online visual detection in such scenes...A fast image segmentation algorithm based on salient features model and spatial-frequency domain adaptive kernel is proposed to solve the accurate discriminate objects problem of online visual detection in such scenes of variable sample morphological characteristics,low contrast and complex background texture.Firstly,by analyzing the spectral component distribution and spatial contour feature of the image,a salient feature model is established in spatial-frequency domain.Then,the salient object detection method based on Gaussian band-pass filter and the design criterion of adaptive convolution kernel are proposed to extract the salient contour feature of the target in spatial and frequency domain.Finally,the selection and growth rules of seed points are improved by integrating the gray level and contour features of the target,and the target is segmented by seeded region growing.Experiments have been performed on Berkeley Segmentation Data Set,as well as sample images of online detection,to verify the effectiveness of the algorithm.The experimental results show that the Jaccard Similarity Coefficient of the segmentation is more than 90%,which indicates that the proposed algorithm can availably extract the target feature information,suppress the background texture and resist noise interference.Besides,the Hausdorff Distance of the segmentation is less than 10,which infers that the proposed algorithm obtains a high evaluation on the target contour preservation.The experimental results also show that the proposed algorithm significantly improves the operation efficiency while obtaining comparable segmentation performance over other algorithms.展开更多
文摘3D terrain visualization of geographic information systems(GIS)data has become an important issue in recent years.This is due to the emergence of new geo-browsers such as Google Earth,widely popular among users.The availability of 3D representation tools has increased the demand for 3D terrain visualization.The aim of this paper is to review the literature related to the 3D terrain visualization of GIS data from the first map produced until the online mapping era.The reviews are divided into four different sections:manual visualization of 3D terrain,automated visualization of 3D terrain,online visualization of 3D terrain,and software for visualizing 3D terrain.Then,the paper compares between the different types of systems developed by various authors based on the capabilities and the limitations of the system.Some of the techniques have their own strengths and limitations which solve the problem in 3D terrain visualization.However,the research on improving 3D terrain visualization is still ongoing.This is due to the popularity of online environments and mobile devices that render 3D terrain.This review paper will help interested users understand the current state of 3D terrain visualization of GIS data in a better way.
基金supported by National Natural Science Foundation of China[grant numbers 61573233]Natural Science Foundation of Guangdong,China[grant numbers 2021A1515010661]+1 种基金Special projects in key fields of colleges and universities in Guangdong Province[grant numbers 2020ZDZX2005]Innovation Team Project of University in Guangdong Province[grant numbers 2015KCXTD018].
文摘A fast image segmentation algorithm based on salient features model and spatial-frequency domain adaptive kernel is proposed to solve the accurate discriminate objects problem of online visual detection in such scenes of variable sample morphological characteristics,low contrast and complex background texture.Firstly,by analyzing the spectral component distribution and spatial contour feature of the image,a salient feature model is established in spatial-frequency domain.Then,the salient object detection method based on Gaussian band-pass filter and the design criterion of adaptive convolution kernel are proposed to extract the salient contour feature of the target in spatial and frequency domain.Finally,the selection and growth rules of seed points are improved by integrating the gray level and contour features of the target,and the target is segmented by seeded region growing.Experiments have been performed on Berkeley Segmentation Data Set,as well as sample images of online detection,to verify the effectiveness of the algorithm.The experimental results show that the Jaccard Similarity Coefficient of the segmentation is more than 90%,which indicates that the proposed algorithm can availably extract the target feature information,suppress the background texture and resist noise interference.Besides,the Hausdorff Distance of the segmentation is less than 10,which infers that the proposed algorithm obtains a high evaluation on the target contour preservation.The experimental results also show that the proposed algorithm significantly improves the operation efficiency while obtaining comparable segmentation performance over other algorithms.
