Optimal spatial scale choosing for high resolution imagery based on texture frequency analysis

Choosing the optimal spatial scale is one of the crucial issues in the field of remote sensing.In this paper,an approach,which is based on texture frequency analysis is proposed to determine the optimal spatial scale for high resolution imagery.Firstly,four typical geo-objects are used to analyze their frequency properties of the response to the Fourier transform domain.Secondly,the original image is up-scaled to different spatial resolutions using point spread function.The adequate spatial scale is chosen according to the change patterns in the radius distribution and angle distribution curves of geo-object texture with up-scaling.Finally,the separability among four types of geo-objects at six scales is analyzed based on the texture feature to approve the feasibility of the new method.The object-based classification of the QuickBird panchromatic image by means of SVM is implemented,and results of experiment demonstrate that the higher accuracy can be obtained at the optimal spatial scale.

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