Affiliation:
1. Teaching and Research Office of Surveying and Mapping, Institute of Water Conservancy Engineering, Hebei University of Water Resources and Electric Engineering, Cangzhou 061001, China
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.
Subject
General Physics and Astronomy
Reference52 articles.
1. Entropy and fractal antennas;Entropy,2016
2. Mapping of groundwater prospective zones integrating remote sensing, geographic information systems and geophysical techniques in El-Qaà Plain area, Egypt;Hydrogeology J,2017
3. A tight neighborhood union condition on fractional (G, F, N′, M)-critical deleted graphs;Colloq Mathematicum,2017
4. Classification of image matching point clouds over an urban area;Int J Remote Sens,2018
5. Classification of image matching point clouds over an urban area;Int J Remote Sens,2018