Abstract
Automatic and reliable multi-sensor image matching is a very challenging task due to the significant nonlinear radiometric differences between multi-sensor images. In this paper, a novel dense descriptor based on adaptive multiscale structure orientation is proposed for capturing the geometrical structure information of an image. The dense descriptor of the proposed matching algorithm is not only illumination and contrast invariant but also robust against the image noise. Further, an improved similarity measurement is introduced for adapting the orientation reversal caused by the intensity inversion between multi-sensor images. Based on the robust dense descriptor and the improved similarity measurement, we developed a novel and practical template matching algorithm to match multi-sensor images reliably. We evaluate the proposed matching algorithm by comparing it with other state-of-the-art algorithms. The experimental results show the proposed algorithm has a significant advantage on matching accuracy.
Highlights
With the rapid development of remote sensing technology, multi-sensor images are more and more extensively used in ground survey [1]
In order to address the above problems, we proposed a novel template matching algorithm based on Adaptive Multiscale Structure Orientation (AMSO)
In this paper we proposed a dense descriptor based on multiscale adaptive structure orientation for multi-sensor image matching
Summary
With the rapid development of remote sensing technology, multi-sensor images are more and more extensively used in ground survey [1]. Template matching algorithm is preferred for matching multi-sensor images which usually contain significant noise and nonlinear radiometric distortion [8], [15]. Template multi-sensor image matching is mainly limited by significant image noise and the nonlinear grayscale distortion [7]–[9]. The proposed algorithm is very robust to complicated grayscale distortion between multi-sensor images because it’s matching images based on the geometric structure information instead of image intensity. A. A NEW DENSE DESCRIPTOR BASED ON MULTISCALE ADAPTIVE STRUCTURE ORIENTATION The gray distortion caused by nonlinear radiometric difference is a great challenge to the multi-sensor image matching. In this paper we proposed a dense descriptor based on multiscale adaptive structure orientation for multi-sensor image matching.
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