Subpixel matching method for remote sensing image of ground features based on geographic information

Chen Chen

doi:10.1515/phys-2020-0101

Abstract

AbstractIn order to solve the problem of large error of subpixel matching and poor filtering effect in traditional methods, a subpixel matching method based on geographical information is proposed. First, the image quality of the remote sensing image is enhanced by the image enhancement method based on light energy allocation. Then, the boundary geographic information is extracted by the improved thresholding segmentation algorithm based on histogram exponential convex hull for the enhanced remote sensing image of ground features. Based on the extracted geographic information, by matching the boundary image with the function measurement method, the center coordinates of the image block corresponding to the actual measurement map and the reference submap which achieve the best matching are obtained. According to the corresponding geometric transformation relationship between the measured image and the reference image, the subpixel matching of the measured remote sensing image and the reference image can be carried out under the least-square-error criterion. The experimental results show that the enhancement performance and noise filtering performance of the proposed method are better than those of the same type of method, the matching residual is very small, the matching accuracy is high, and the application value is significant.

Highlights

As the main content of computer vision and image processing, image matching research has importantIn the past few decades, various image matching algorithms have emerged and combined with many mathematical theories and methods, people have constantly proposed new matching methods
Subpixel matching method for remote sensing image of ground features based on geographic information 279 pixel points to obtain the main direction of feature points
Taking the satellite remote sensing image of Wenchuan earthquake as an example, Figure 2 is the satellite remote sensing image of Wenchuan earthquake before the processing of the proposed method, and Figure 3 is the satellite remote sensing image of Wenchuan earthquake after the processing of the proposed method: It can be seen from the comparison between Figures 2 and 3 that the resolution of the satellite remote sensing image of the Wenchuan earthquake enhanced by the method in this paper has been improved, and the geographic information in the image is more significant

Summary

Introduction

As the main content of computer vision and image processing, image matching research has importantIn the past few decades, various image matching algorithms have emerged and combined with many mathematical theories and methods, people have constantly proposed new matching methods. Subpixel matching method for remote sensing image of ground features based on geographic information 279 pixel points to obtain the main direction of feature points. The polar coordinates are constructed with the feature points as the origin, the neighborhood of the feature points is segmented, and the feature vectors are obtained by combining the distribution histograms in the segmented region, to form the feature descriptors. On this basis, the Euclidean model is used to calculate the ratio of the nearest neighbor to the neighbor of the feature points and complete the image pixel matching. The experimental results show that the matching accuracy error of the algorithm is small, but the filtering effect is not good [4]

Methods

Results

Discussion

Conclusion