Abstract: Aiming at the problem that feature extraction accuracy and algorithm robustness cannot be taken into account in the existing high-resolution remote sensing image perception Hash authentication algorithms, this paper proposes a high-resolution remote sensing image perception Hash integrity authentication algorithm using ULBP. Firstly, the remote sensing image was divided into grids, and the image is divided into multiple sub-blocks. ULBP algorithm is used to extract the texture features of sub-blocks. Then, the histogram distribution of texture feature in each sub-block is calculated and the perceived hash sequence of sub-block is obtained after binarization of the result and the mean value. Finally, the perceptive Hash sequence of all sub-blocks is concatenated to generate the perceptive hash value of the whole image. In image authentication, the Hash sequence of the original image and the image to be detected is first calculated, and then the average hamming distance of the perceived Hash sequence of the two is calculated, so as to complete the integrity authentication and tamper location of the high-resolution image content. Experiments show that the algorithm can identify the relatively smooth areas of ground objects in high-resolution remote sensing images, and has good robustness for the maintenance of contents such as JPEG compression, Gaussian noise and BMP format conversion, thus providing support for the integrity authentication of high-resolution remote sensing images.

Key words: perceptual Hash, ULBP, high-resolution image, content authentication, textural features