Abstract: The quality of mine remote sensing image is affected by the imaging regional environment greatly,and the imaging device inherent defects make access to the obtained remote sensing image with certain degree of distortion,which appeared all kinds of random noise.The median filtering (MF)algorithm is weighted improved,a new adaptive weighted improved median filtering(AWIMF) algorithm that is suitable for remote sensing image processing is proposed.Firstly,the image is divided into many image blocks with the size of 7×7,the maximum and minimum pixel gray values of each image block are counted out,and the pixels are marked as the class one suspected noise points;secondly,the pixel gray median values of each image block are calculated,each pixel gray value of the each image blocks and its corresponding pixel gray median values are made differential operation,the pixels corresponding with larger differential values are marked as the class two suspected noise points,the pixels that are marked as the suspected noise points in the process of noise detection are identified as noise points;thirdly,centered with each noise points,the filter windows with the size of 5×5 are selected,based on the each pixel gray values in the filtering windows and the gray median values of the corresponding filtering windows,the weighted values are calculated,each pixel gray value and its corresponding weighted value are conducted weighted calculation to filtering out the noise points effectively;finally,the filtered remote sensing image contrast is adjusted by adopting the histogram specification (HS) algorithm,the remote sensing image of Baiyun Obo mining area,Inner Mongolia is used as the experimental data,the experimental results show that the performance of the algorithm proposed in this paper is superior to median filtering (MF) algorithm and its several existing improved algorithms.

Key words: Mine remote sensing image, Median filtering, Suspected noise point, Weighted improved median filtering, Histogram specification