Research On Region Target Semi-automatic Extraction Of Rs Images Based On Texture Features

With the development of technologies of sensor, aerial and space platform, and data communication, remote sensing technique has entered a new era that can obtain various earth data actively, rapidly, accurately, and through multi-way. It possesses omni-directional and all-weather ability to acquire space information. Therefore, it is an important data source to update spatial information, and have extensive application potential in national economy and military affairs. As far as the interpretation of spatial images and the digitization work in surveying and mapping field are concerned, this paper has researched a method, based on texture features of remote sensing images, to semi-automatically extract canonical area symbol. The key contents of the method are texture feature extraction, feature matching, and region extraction etc.The major works of this paper are listed as follows:1. The concept, significance, difficulty of remote sensing image interpretation is introduced. Current status and developing trend of area symbol extraction from remote sensing images is analyzed. Based on texture features, relating technologies of area symbol extraction are discussed.2. Experiments on different texture features are done for a general area symbol extraction algorithm. Then, based on the experimental results, the algorithm is analyzed and improved.3. Based on Log-polar transformation and Fourier transformation, settlement place extraction algorithms are analyzed and improved. Then, a new algorithm which combine radon transformation with tree-structure wavelet transforms is proposed. Experimental results prove that the algorithm can ideally extract settlement places from panchromatic remote sensing images of different scales.4. Three affine-invariant extraction techniques, which are based on multi-scale framework, are thoroughly analyzed and investigated. Experiments are done on various canonical area symbols. The experimental results prove that the semi-automatic extraction process can be accomplished accurately, and therefore possesses great practicality.