[A method of object detection for remote sensing-imagery based on spectral space transformation].

Object detection is an intermediate link for remote sensing image processing, which is an important guarantee of remote sensing application and services aspects. In view of the characteristics of remotely sensed imagery in frequency domain, a novel object detection algorithm based on spectral space transformation was proposed in the present paper. Firstly, the Fourier transformation method was applied to transform the image in spatial domain into frequency domain. Secondly, the wedge-shaped sample and overlay analysis methods for frequency energy were used to decompose signal into different frequency spectrum zones, and the center frequency values of object's features were acquired as detection marks in frequency domain. Finally, object information was detected with the matched Gabor filters which have direction and frequency selectivity. The results indicate that the proposed algorithm here performs better and it has good detection capability in specific direction as well.