Geng Zhen-wei, Jiang Yong-mei, Su yi, Yu Wen-xian. An Approach to Airport ROI Detection in Large Remote Sensing Images[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1770-1773.
Citation:
Geng Zhen-wei, Jiang Yong-mei, Su yi, Yu Wen-xian. An Approach to Airport ROI Detection in Large Remote Sensing Images[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1770-1773.
Geng Zhen-wei, Jiang Yong-mei, Su yi, Yu Wen-xian. An Approach to Airport ROI Detection in Large Remote Sensing Images[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1770-1773.
Citation:
Geng Zhen-wei, Jiang Yong-mei, Su yi, Yu Wen-xian. An Approach to Airport ROI Detection in Large Remote Sensing Images[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1770-1773.
Object detection has been a difficult problem in remote sensing community for a long time. To process very large image make object detection even more difficult. A method for detecting airport ROI(Region Of Interest) is proposed, which is based on feature space analysis that can fast locate airport. The image can be read into blocks for extracting features respectively and simultaneously. The extracted features are analyzed by mean-shift method, and eventually the airport regions can be located. The proposed ROI detecting method has strong robustness, autonomy and parallelism. It can drastically decrease the difficulty of processing very large images.
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