isprs archives XLI B7 83 2016
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Two main processes were involved: (1) automatic extraction of building roofs using the integration of LiDAR data and aerial imagery in order to derive its’ outline and areal
Figure 2: Change detection examples (1st-4th row): Previous image (1st column), current image (2nd column), masks of feature based approach (3rd), extended image differences using a 7
GROUND DEFORMATION EXTRACTION USING VISIBLE IMAGES AND LIDAR DATA IN MINING AREAa. Wenmin Hu a,b , Lixin
KEY WORDS: Polarimetric Synthetic Aperture Radar (PolSAR), Unsupervised Wishart Classification, Fisher Linear Discrimination, Feature
Inspirited by the thresholding-based methods, ACCA ( Irish et al., 2000 ) and Fmask ( Zhu et al., 2012 ), several spectral bands and band radios that defined according
In the first basic configuration (Config.1), only one defined feature is used for feature extraction at each experiment, for which parameters are set manually
KEY WORDS: Vision Based Localization, Local Bundle Adjustment, Feature Extraction, performance
KEY WORDS: terrestrial laser scanning, range noise, data resolution, joint roughness, wavelet transform, non-local mean, denoising
