With the continuous development of remote sensing technology, the resolution of remote sensing image is gradually improving, and the information contained in high resolution remote sensing image is also more rich, which is widely used in various fields. The extraction of buildings using high resolution remote sensing image has also become one of the research hotspots. In order to solve the problems of incomplete or missing buildings detected by traditional building detection algorithms in high resolution remote sensing images, and the similarity of spectral features between buildings and roads and bright soil is difficult to distinguish. The purpose of this study is to develop an effective building extraction algorithm based on improved adaptive MBI index based on GF-2 satellite data. First radiation calibration in remote sensing image preprocessing, such as the original image from the RGB space transformation to do after YCbCr space information, and to adaptive image enhancement processing, feature extraction with adaptive body mass index, and using vegetation index set threshold value of buildings and shadow region, the preliminary extraction result post-processing of the building, So as to get the final extraction result. Compared with the traditional building morphological index MBI algorithm, the error of error and error of missing classification are reduced, and the overall accuracy is improved by about 20%.
|