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Leilei Geng
Nanjing University of Science and Technology, Nanjing

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Adaptive Wallis Filter via Sparse Recognition for Automatic Control Points Extraction Leilei Geng; Deshen Xia; Quansen Sun; Kai Yuan
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 4: April 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

With the rapid development of the remote sensing satellite, the size and the resolution of satellite images grow increasingly. The evaluation of remote sensing image quality requires precise information of control points extracted from unevaluated images and reference images. Therefore, we propose an adaptive Wallis filter method based on sparse recognition to increase the number of control points and improve the matching precision. Firstly, feature vectors of images are constructed by computing the image radiation-parameters. Secondly, the classification of sub-region terrain in the image can be determined using sparse recognition. Finally, according to specific type of sub-region terrain, we enhance the regions by the Wallis filter based on corresponding filter parameters and extract control points which would lead to the automatic evaluation for geometric precision. The experiments show that the proposed method can get better results especially in the detail on the images of Resourse-3 satellite, hence can increase the number and improve accuracy of control points. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4781
Co-Authors Deshen Xia Kai Yuan Quansen Sun