Rama Rao Nidamanuri

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Hyperspectral image contains fine spectral and spatial resolutions for generating accurate land use and land cover maps. Supervised classification is the one of method used to exploit the information from the hyperspectral image. The traditional supervised classification methods could not be able to overcome the limitations of the hyperspectral image. The(More)
Multiview registration is an important part of the 3D modeling pipeline and it aims to bring all the partial views of a model in to a common co-ordinate system. In case of availability of redundant overlap area among the partial point clouds, motion averaging provides an efficient solution to the multiview registration problem. The averaging of underlying(More)
Point clouds data acquired from airborne LiDAR point cloud data sources have great ability to provide vital structural information about geospatial objects. Identification, segmentation and visualization of airborne LiDAR point cloud data is interesting but considerably challenging problem. Processing LiDAR point cloud data can reveal several interesting(More)
Registration of partially overlapping 3D point clouds of an object is the initial phase in the 3D modeling pipeline. The automatic coarse alignment of a pair of 3D images is usually performed by 3D feature matching. Robust estimators like RANSAC are employed for 3D transformation estimation from point correspondences obtained by feature matching, in the(More)
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