Robust detection of significant points in multiframe images1
Significant point (SP) detection is an important pre-processing step in image registration, data fusion, object recognition and in many other tasks. This paper deals with multiframe SP detection, i.e. detection in two or more images of the same scene which are supposed to be blurred, noisy, rotated and shifted with respect to each other. We present a new method invariant under rotation that can handle differently blurred images. Thanks to this, the point sets extracted from different frames have relatively high number of common elements. This property is highly desirable for further multiframe processing. The performance of the method is demonstrated experimentally on satellite images.
blurred image point detection rotation invariance multiple frames remote sensing