A remote sensing image matching algorithm based on the feature extraction

Authors:
Chengdong Wu;Chao Song;Dongyue Chen;Xiaosheng Yu
Affiliations:
College of Information Science & Engineering, Northeastern University, Shenyang, China;College of Information Science & Engineering, Northeastern University, Shenyang, China;College of Information Science & Engineering, Northeastern University, Shenyang, China;College of Information Science & Engineering, Northeastern University, Shenyang, China
Venue:
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Year:
2012

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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.