ESTIMATION OF OPTIMAL PARAMETER FOR RANGE NORMALIZATION OF MULTISPECTRAL AIRBORNE LIDAR INTENSITY DATA
نویسندگان
چکیده
منابع مشابه
A Normalization scheme for Terrestrial LiDAR Intensity Data by Range and Incidence Angle
Automatic registration, classification and segmentation of Terrestrial Laser Scanner (TLS) data are of great interest in Geoinformatics & Autonomous vehicle research. Along with dense and accurate 3D geometric data, laser scanners also collect return intensity information. Inclusion of this spectral information has potential to improve the working of the above mentioned processes. However, thes...
متن کاملIntensity Normalization by Incidence Angle and Range of Full-waveform Lidar Data
The analysis of LIDAR data to extract surface features is of great interest in photogrammetric research. Our investigations show that the same material of a surfaces (e.g. gabled roof) yields to different measured values for the intensity due to the incidence angle. These values are strongly correlated to the incidence angle of the laser beam on the surface. Therefore we improve the value of th...
متن کاملNormalization of Lidar Intensity Data Based on Range and Surface Incidence Angle
The analysis of airborne laser scanner data to extract surface features is of great interest in photogrammetric research. Especially for applications based on airborne measurements, where the intensity is crucial (e.g. for segmentation, classification or visualization purposes), a normalization considering the beam divergence, the incidence angle and the atmospheric attenuation is required. Our...
متن کاملMerging Surface Reconstructions of Terrestrial and Airborne LIDAR Range Data
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission....
متن کاملParameter Estimation for Bayesian Classification of Multispectral Data
In this paper, we present two algorithms for estimating the parameters of a Bayes classifier for remote sensing multispectral data. The first algorithm uses the Support Vector Machines (SVM) as a multi-dimensional density estimator. This algorithm is a supervised one in the sense that it needs in advance, the specification of the number of classes and some training samples for each class. The s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
سال: 2020
ISSN: 2194-9050
DOI: 10.5194/isprs-annals-v-3-2020-221-2020