搜索结果: 1-6 共查到“multi-spectral images”相关记录6条 . 查询时间(0.13 秒)
Automated Updating of Building Data Bases from Digital Surface Models and Multi-Spectral Images: Potential and Limitations
Change Detection Digital Surface Models Data Fusion
2015/12/4
A method for automatic updating of building data bases from Digital Surface Models (DSM) and a normalised difference vegetation index is evaluated. The DSM can be generated from Airborne Laserscanner ...
OBJECT-ORIENTED CHANGE DETECTION OF RIPARIAN ENVIRONMENTS FROM HIGH SPATIAL RESOLUTION MULTI-SPECTRAL IMAGES
Object-Oriented Change Detection Definiens Developer Rule Sets Riparian Zones
2015/11/16
The objectives of this research were to: (1) develop rule sets in Definiens Developer 7® for mapping and monitoring riparian zone
land-cover classes within two QuickBird images; and (2) compare...
Classification of multi spectral images by fuzzy and neural network approaches
fuzzy classification minimum distance maximum likelihood
2015/8/20
Extraction of information from satellite images, due to better cost & time consumption, all times accessibility and vast area of
coverage, is seen as one solution for countries have no overall maps [...
Automating Interpretation of Geological Structures from Landsat Tm Multi-spectral Images and Dems
nterpretation Extraction Classification
2015/7/9
In this study using the Idrisi software system, a methodology for jointly analyzing and interpreting multi-spectral images and DEMs
for extracting structural-geology features is given. In analyzing a...
MODELLING QUALITATIVE AND QUANTITATIVE UNCERTAINTIES OF OBJECTS EXTRACTED FROM HIGHRESOLUTION MULTI-SPECTRAL IMAGES AND LASER SCANNING DATA
Quality Uncertainty Object Extraction
2015/6/1
An object-based approach is applied in land-cover feature extraction from high-resolution multi-spectral images and laser scanning
data in this research. Objects extracted from high-resolution spect...
基于多光谱图像及组合特征分析的茶叶等级区分（Classification of Tea Grades by Multi-spectral Images and Combined Features）
茶叶等级 多光谱成像 形状特征 纹理特征 组合特征
2009/11/3
提出了一种采用多光谱成像的机器视觉技术对4个等级的西湖龙井茶进行区分的方法。首先采用3CCD多光谱摄像机同时获取茶叶在540、670和800nm波谱处的波长图像，然后对预处理后的图像进行图像特征提取，选取了18个形状特征和15个纹理特征。基于这2组特征分别对4个等级的茶叶进行主成分聚类分析，得到的两幅主成分空间的聚类图都不能对4个等级茶叶进行有效的区分。为了得到高效的区分模型，本研究对形状特征和纹...