With the development of remote sensing imaging technology and the improvement of multi–source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .
In this paper, we discuss the problem of sum rate improvement for coded MIMO interference system, and propose joint beam design and user selection over interference channel. Firstly, we have formulated non-binary LDPC coded MIMO interference networks model. Then, the least square beam design for MIMO interference system is derived, and the low complexity user selection is presented. Simulation results confirm that the sum rate can be improved by the joint user selection and beam design comparing with single interference aligning beamformer.