Title :
Research on Adaptive Classification Algorithm of Remote Sensing Image
Author :
Yuanmin Fang ; Jie Chen ; Yonghua Xia ; Weiwei Song ; Yongming Yang
Author_Institution :
Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
With the rapid development of remote sensing technology, the information contained in an image becomes more and more comprehensive. Therefore, how to automatically extract information of interest from image data has become a hot topic. In this paper, the automatic airborne remote sensing image classification algorithm is studied by the use of image pyramid. First, the airborne remote sensing image is divided into several tiles to reduce the amount of data processed at the same time; second, Gaussian smoothing is carried in the studied area in order to weaken the influence of noise; third, image pyramid is established according to the different image scale of the target area; fourth, Canny boundary recognition processing is done in the original image; in the end, a package of stable boundary information is obtained by analyzing the objects\´ features in different image scale based on the theory "different objects have different performance under different resolutions". Aerial photographs are taken for experiment, the results prove that the algorithm can classify the boundary information effectively. The final classification results can be applied to a series of operations after lined edge procession.
Keywords :
Gaussian processes; edge detection; feature extraction; geophysical image processing; image classification; remote sensing; Canny boundary recognition processing; Gaussian smoothing; adaptive classification algorithm; aerial photograph; automatic airborne remote sensing image classification algorithm; automatically information extraction; different image scale; image pyramid; lined edge procession; object feature analysis; stable boundary information; Classification algorithms; Feature extraction; Image edge detection; Image resolution; Noise; Smoothing methods; Tiles;
Conference_Titel :
Image and Data Fusion (ISIDF), 2011 International Symposium on
Conference_Location :
Tengchong, Yunnan
Print_ISBN :
978-1-4577-0967-8
DOI :
10.1109/ISIDF.2011.6024246