A Review on the Application of Visual Attention in Target Detection of Remote Sensing Image

Abstract

Target detection in remote sensing image is critical for remote sensing applications such as area Inspection, passive navigation, disaster salvation, aero craft guiding, etc. The detection effect of classical target detection methods is not ideal for problems such as remote sensing image data for large, complex backgrounds, or the target's own lack of information. This paper carries up the analysis of certain difficult problems which exist in remote sensing image target detection, the research results, the massive existing models in which solves using Itti and the Koch vision attention model and its improvement model. As can be seen from the analysis, bottom-up visual attention model was used for the rapid detection of the target of interest in remote sensing images; increases target detection efficiency and accuracy, through a combination of the top-down visual attention model. As can be seen from the examples of the successful applications of remote sensing image target detection, visual attention can effectively capture important information: real-time and robustness strong.