导航

ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2014, Vol. 35 ›› Issue (1): 240-248.doi: 10.7527/S1000-6893.2013.0326

• Electronics and Control • Previous Articles     Next Articles

A Feature Point Extraction Method for Large Size Aerial Images

SHI Xiangbin1,2, ZHANG Jinsong2, CHEN Runfeng2, LIU Jinli2   

  1. 1. College of Computer Science, Shenyang Aerospace University, Shenyang 110136, China;
    2. College of Information, Liaoning University, Shenyang 110136, China
  • Received:2013-04-07 Revised:2013-06-28 Online:2014-01-25 Published:2013-07-12
  • Supported by:

    National Natural Science Foundation of China (61170185);Scientific and Technological Research Projects in Liaoning (2011217002)

Abstract:

The existing feature point extraction methods usually cost a lot of CPU time when they are applied to large size aerial images. For the purpose of fast extraction of feature points in these large size aerial images, a novel method is developed. Usually these aerial images have not only large sizes but also wide ranges of shooting. They usually have different feature point performances on different scales and the distributions of spectra are uniform in the frequency domain. In this paper, the scales of the feature points are kept by employing the Laplacian pyramid, and a specified non-uniform N-dimensional directional filter bank is applied to decompose the pyramid images. The scales and the directions of the images are extracted. Then the local extreme points are extracted as a candidate feature points set. Finally, the candidate feature points in different directions are merged by a specified merge-strategy. Thus, we obtain the final feature points set and the directions of the feature point described by the direction filter bank. Experimental results are presented that demonstrate the proposed method is efficient for large size aerial images while meeting the match rate and precision rate requirements.

Key words: aerial image, feature point extraction, feature point matching, Laplacian pyramid, directional filter bank

CLC Number: