Abstract
In this paper, a novel method for remote sensing image matching through mean-shift is proposed. First, state of the improved Mean-shift is reminded. Primary mean-shift algorithm is only based on color feature, but color feature does not apply to the remote sensing images matching. This paper exhibits a method to solve this problem using the gradient direction histogram instead of the color histogram. Secondly, Speeded-Up Robust Features (SURF) is applied to the fine matching. The experimental results show that the improved mean-shift matching algorithm, combining to the surf detector can realize two images matching accurately. © 2012 Springer-Verlag.
Author supplied keywords
Cite
CITATION STYLE
Wu, C., Song, C., Chen, D., & Yu, X. (2012). A remote sensing image matching algorithm based on the feature extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7368 LNCS, pp. 282–289). https://doi.org/10.1007/978-3-642-31362-2_32
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
