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Journal of Sensors
Volume 2015, Article ID 415361, 9 pages
http://dx.doi.org/10.1155/2015/415361
Research Article

Automatic Fusion of Hyperspectral Images and Laser Scans Using Feature Points

1Research Center of Artistic Heritage, Taiyuan University of Technology, Taiyuan 030012, China
2Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China

Received 14 November 2014; Accepted 7 February 2015

Academic Editor: Xue Cheng Tai

Copyright © 2015 Xiao Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.