automatic fusion of hyperspectral images and laser scans using feature points

Clicks: 94
ID: 138148
2015
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Ranked #181 of 205 articles by views in BMC infectious diseases

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Abstract
Automatic fusion of different kinds of image datasets is so intractable with diverse imaging principle. This paper presents a novel method for automatic fusion of two different images: 2D hyperspectral images acquired with a hyperspectral camera and 3D laser scans obtained with a laser scanner, without any other sensor. Only a few corresponding feature points are used, which are automatically extracted from a scene viewed by the two sensors. Extraction method of feature points relies on SURF algorithm and camera model, which can convert a 3D laser scan into a 2D laser image with the intensity of the pixels defined by the attributes in the laser scan. Moreover, Collinearity Equation and Direct Linear Transformation are used to create the initial corresponding relationship of the two images. Adjustment is also used to create corrected values to eliminate errors. The experimental result shows that this method is successfully validated with images collected by a hyperspectral camera and a laser scanner.
Reference Key
zhang2015journalautomatic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Xiao Zhang;Aiwu Zhang;Xiangang Meng
Journal BMC infectious diseases
Year 2015
DOI
10.1155/2015/415361
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