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Efficient Segmentation and Classification of Remote Sensing Image Using Local Self Similarity

Karthikeyan.K, Thiruselvi.M

Segmentation and classification are important role in remote sensing image analysis. Recent research shows with the aim of images can be described in hierarchical structure or regions. In this project, we submit application graph laplacian energy as generic measure for segmentation. We capture in geometric outline of region in an image by using apply local self similarity features. This paper finds application in remote sensing image analysis. It decreases the redundancy in the hierarchy by order of magnitude with small loss or performances. We have achieved better performance from graph laplacian energy method. I improve the efficiency using unsupervised learning.