Mining the features of spatial adjacency relationships to improve the classification of high resolution remote sensing images based on complex network

Due to the complexity of spatial and structural patterns of remote sensing images, land cover classification is still an active, ongoing problem in the field of image classification. The limited spectrum and texture features can be used often lead to low accuracy in remote sensing image classifications. Spatial structure information, which is commonly regarded as very useful information for improving land cover classifications, characterizes a composite of several types of objects or land covers. However, it is rarely used because it is difficult to describe and calculate. Generally, images contain the relationships of spatial adjacency, spatial direction and spatial distance among multiple objects. This study selects spatial adjacency relationships as an example, mines the features of spatial adjacency, and uses to improve classification. Therefore, this paper (1) presents a modeling method of remote sensing images based on complex networks to express the spatial structure information and make it computable firstly; (2) gives network expression and calculation methods of spectrum, texture and object features in images; (3) discusses a discovery method of spatial adjacency feature based on network. Finally, this paper gives a strategy to improve the classification for high-resolution image by using the spatial adjacency features. Two kinds of data in coastal zones and city areas are used to verify the method. The results show that the proposed approach, which considers the features of spatial adjacencies, improves the classification accuracy by at least 4% compared with the approaches that do not consider spatial adjacencies. Comparing with the results of deep learning method, our method has higher overall accuracy when the numbers of samples are small. •A modeling method of remote sensing images based on complex networks is presented.•Algorithms of calculating the features of images based on networks is given.•A method for discovering spatial adjacency features based on network is developed.•A classification method of high-resolution images is proposed.