Abstract: Gray-level image analysis is important in shale pore structure characterization. To obtain good imaging re- sult,it is necessary to adjust the brightness and contrast for the different fields of view or different samples when captu- ring the image. This will bring difference in gray-level distribution,which directly results in the variation of threshold value for pores. To solve this problem,the SEM image was taken as an example to analyze the factors that can influence the grey level of image. The grey level distribution of the uncorrected image is represented by the integrated cumulative probability distribution of the references,which are based on the density probability distribution extracted from the py- rites,authigenic quartz,organic matter and pore in shale. By establishing relations with the standardized image,the cor- rection can be realized based on the theory of gray level histogram specification. The results show that the grey-level distributions of the marker assemblage can cover the whole grey-level range of the image. Due to the adoption of the marker assemblage,the influence of the shale compositions on the grey level of the image can be eliminated and the discrepancies in the grey level of image induced by different scanning parameters of brightness and contrast can be corrected. The effect of image standardization was verified and it can be applied to images scanned under different situ- ations. The results show that the proposed standardization method can improve the automatic identification of pore and organic matter by using the same threshold value,which will lay a solid foundation for microscopic image analysis and provide comparable and reliable data for the quantitative characterization of shale pore structure.