Abstract
This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels.
Highlights
With the rapid development of unmanned aerial vehicle (UAV) technology, we urgently need a low cost multispectral system which can acquire multispectral images at the wavelengths based on actualSensors 2015, 15 requirements
In light of this, according to the structural characteristics of the four-camera multispectral system, this paper proposed an effective method to remove most of the false matches and greatly increase the correct rate, and uses the random sample consensus (RANSAC) to eliminate the remaining false matches
The second part describes the derivation of the matching model and its parameters calculation method; the third part introduces the method of eliminating false matches; the fourth part shows the different band image registration experiments; the fifth part shows the data acquisition and accuracy assessment; and the final part gives a conclusion
Summary
With the rapid development of unmanned aerial vehicle (UAV) technology, we urgently need a low cost multispectral system which can acquire multispectral images at the wavelengths based on actual. It is a very complex system, and the multispectral system is only one of its subsystems Most of these four papers focus on hardware design and data synchronization acquisition but fail to introduce alignment methods in detail. In light of this, according to the structural characteristics of the four-camera multispectral system, this paper proposed an effective method to remove most of the false matches and greatly increase the correct rate, and uses the RANSAC to eliminate the remaining false matches. The second part describes the derivation of the matching model and its parameters calculation method; the third part introduces the method of eliminating false matches; the fourth part shows the different band image registration experiments; the fifth part shows the data acquisition and accuracy assessment; and the final part gives a conclusion
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
