The grayscale changes caused by uneven illumination and sudden changes in illumination affect the detection effect of image features.Therefore,an adaptive FAST-9-12 corner detection algorithm based on grayscale mean value is designed.Firstly,a small-area double-detection template is designed based on the extensibility of feature points,which reduces the number of comparisons between pixels and central points,and improves the region positive detection rate and detection speed.Secondly,based on the local grayscale mean value of the image,the threshold is adaptively adjusted in the detection template of each pixel to avoid the impact of grayscale changes on the detection effect.Finally,the corner radius suppression principle is designed according to the idea of flexible non-maximum suppression so as to screen more robust corners.The experimental results on the dataset of Inria remote sensing images show that the corner detection speed of FAST-9-12 is about 22% higher than that of FAST-12-16 and FAST-9-16 templates,and since the extraction method of adaptive threshold is not easily affected by the illumination,the detection accuracy is improved by 4.16 and 3.11 percentage points respectively.FAST-9-12 realizes rapid and accurate detection of image features.