Novel airport region recognition method in low visibility infrared image

Background clutters are usually complicated while contrasts of targets are usually low in low visibility infrared image. On account of this, a new airport recognition method is presented in this paper based on the region-of-interest extracting algorithm and the region growing algorithm. The method is made of four parts. Firstly, image pre-processing is done with adaptive wiener filtering to suppress image background clutters and to improve signal-to-noise of targets. Secondly, image fusion threshold is done applied two threshold methods based on the gray distribution difference between airport and image background clutters, the one is adaptive two-threshold segmentation and another is the adaptive local range segmentation. Thirdly, using airport region shape character and length-width-ratio of airport, the region-of-interest of airport is found via morphology processing and connected-domain-label algorithm. Finally, airport region is recognized applied region growing with prior image constraint. This method takes advantages of the region-of-interest extraction method and region growing method. And it can recognize airport in integrity with lower computational complexity. Some experiments show that the proposed method has good performance of detecting and recognizing airport region in low visibility infrared images.