Research On High Resolution Remote Sensing Image Classification Technology

The development of the remote sensing technology makes us obtain very abundant information of nature, especially with the appearance of high resolution remote sensing image it extends the visual field of the nature. But the challenge that faces us is how to make use of the data effectively and obtain more useful information through some processing. High resolution remote sensing data such as QuikBird and IKONOS have a lot of characteristics such as spectral, shape, texture and context and so on compared to the other remote sensing data. Though the technology of the remote sensing image classification has made considerable progress, it will result in not only reducing the classification accuracy but also making the spatial data redundant and wasting the resource when the single traditional classification method is applied to the high resolution remote sensing image.So, with the IKONOS data as the main source, this thesis discusses the classification algorithms and scale-effect which affect the classification accuracy in order to improve the high resolution remote sensing image classification accuracy. The new classification algorithms suitable for the high resolution remote sensing image are brought forward and the relationship between the classification accuracy and the scale effect is discussed.This dissertation includes the following research products and originalities:1) Based on the research of the traditional classification, brings forward a multiple classifier system with a mixed combining rule for decision not a single rule to improve the classification accuracy. Apply the support vector machine to the high resolution remote sensing image classification.2) Study the object-oriented classification technology of high resolution remote sensing image. Combined with the information obtained from the high resolution remote sensing image, three multi-scale, multi-characteristic image segmentation algorithms were brought forward.3) Bring forward a supervised fuzzy classification algorithm with multiple...