## 1 Introduction  
High-resolution remote sensing (HRRS) images have come to play an increasingly important role in urban planning, surveying, mapping, and land use. However, the implicit prerequisite for using HRRS images is that the images can be trusted. If tampered HRRS images are used, erroneous analytical conclusions may be drawn and wrong decisions may be made. Several sets of comparisons (before and after HRRS images were tampered with) are shown in Figure 1. Without integrity authentication technology, it would be difficult for users to determine whether the HRRS image shown in Figure 1b had been tampered with. In such a case, the credibility and value of the HRRS image would be reduced, even losing its value entirely. Tampering with HRRS images, similar to the above, not only reduces the credibility of HRRS images, but also negatively impacts social stability. For example, if a city planning department uses HRRS images that have been tampered with, it may lead to incorrect planning. If a military department uses HRRS images that have been tampered with, it may issue incorrect instructions. Although integrity authentication methods, such as fragile watermark, cryptographic hash, and perceptual hashing solve the above problems to a certain extent, there is still considerable room for improvement. The most prominent problem is that mainstream integrity authentication technologies are oriented to general integrity authentication problems. Thus, they cannot solve the authentication problem in a specific field. Compared with ordinary images, HRRS images mainly reflect the characteristics of ground objects and often have no clear theme; this makes HRRS images more difficult than ordinary images for the human eye to recognize. In actual tampering of HRRS images, attackers often add or remove specific types of image content instead of modifying images at will. This kind of content-biased behavior is inherently subject-sensitive and is more concealed and harmful than random tampering. Moreover, due to the human visual attention mechanism, alteration of the region of interest to the human eye is more noticeable and more damaging to HRRS images. For example, in the examples shown in Figure 2, although the area of Figure 2b that had been tampered with was even smaller than that of Figure 2c, the tampering in Figure 2b was more destructive to HRRS, especially for users for whom buildings are the main object of use. Figure 1: Comparisons before and after HRRS image tampering: (**a**) original images, (**b**) tampered-with HRRS images. From left to right, the alterations of each figure are: a building in the enclosed area replaced with trees, a building added to the enclosed area, a building in the enclosed area defaced, and buildings in the enclosed area deleted. Photoshop is the tool used to tamper with the images. Figure 2: Comparison of subject-related and subject-unrelated tampering (taking buildings as an example of a subject): (**a**) original HRRS image, (**b**) subject-related tampering, (**c**) subject-unrelated tampering. As a new data security technology derived from perceptual hashing [1; 2; 3; 4; 5], subjective-sensitive hashing [6] can perform more stringent integrity authentication on image areas of interest to users. However, subject-sensitive hashing methods still have certain deficiencies, especially since subject-sensitive hashing has not been proposed for a long time. The outstanding problem is that the robustness of existing subject-sensitive hashing algorithms require further improvement in order to meet actual authentication needs. The most typical problem is that the robustness against JPEG (Joint Photographic Experts Group) compression is not ideal. The success of Transformer [7] in multiple research fields has provided new research ideas for solving the existing problems of subject-sensitive hashing. [PERSON] et al.