Based on Spatial Pyramid Matching method

aiming at the insufficient utilization of spatial information

firstly

local position feature is extracted by computing relative position distribution of each dictionary vector in image.Then

global contour feature is generated through Nonsubsampled Contourlet Transform and Linear Discriminant Analysis.Finally

Spatial information is enhanced by combining local position feature with global contour feature

which consequently improves the accuracy of scene and object classification.Extensive experiments are performed on Caltech 101

MSRC and 15 Scene datasets respectively.The experimental results show that the proposed method further utilizes the spatial information

and thus improves the accuracy of image classification.