Application of a Three-Stage Procedure for Extracting a Small-Sized Anchor Object on a Noisy Image

Abstract

The purpose of the article is to develop a three-stage procedure for identifying an anchor object in a noisy current image. This goal is achieved by determining the sampling threshold levels at which the greatest similarity of the compared images is ensured; development of a procedure for refining the maximum of the decision function by quantizing the current image. The solution to the first problem is based on the formation of a correlation field of radio brightness temperatures and the choice of a sampling threshold. It is proposed to use the cross-correlation coefficient as a criterion for the degree of image matching. The effectiveness of the procedure for selecting a fragment of a reference image is assessed based on the criterion of the probability of selecting a fragment of a reference image. It is shown that image noise can lead to a decrease in the probability of selecting a fragment of a reference image, down to 0.4. It is proposed to refine the maximum of the decision function based on the iteration method. The most significant results are the obtained dependences of the probability of choosing a fragment of the reference image on the threshold value and the signal-to-noise ratio, as well as the analytical relation for the asymptote of this dependence. The novelty of the work lies in the fact that the procedure for forming the decisive function has been further developed. This will significantly improve the operating efficiency of unmanned aerial vehicles, especially in conditions of interference.

Keywords

• unmanned aerial vehicle
• three-stage procedure for forming the decision function
• image discretization and quantization
• probability of choosing a fragment of the reference image.