The existing discrete cosine transform (DCT) differential quantization robust watermarking has poor robustness against JPEG compression, cropping, and combined attacks. To improve such issues, a pair of adjacent block coefficients are selected to reduce the offset and improve the robustness of the watermarking. Firstly, at adjacent positions of neighboring blocks, the differences of medium frequency coefficients are calculated, and then the differences are used to divide regions. Experimental results show that this method is more robust to various attacks than the existing DCT differential quantization robust watermarking. The accuracy of watermark extraction under a JPEG compression attack increased by 2%, while the error rates of watermark extraction under a cropping attack and a combination attack decreased by 4.4% and 9%.

Improved encryption devices place higher demands on the randomness and security of encrypted images. Existing image encryption optimization methods based on single- or multi-objectives concentrate on selecting keys and parameters, resulting in relatively fixed parameters and keys that are susceptible to leakage and cracking. Despite the possibility of increasing security, the DNA coding encryption method does not fully take into account the large capacity of image data and the difference between pixels, resulting in a limited level of randomness. To overcome the problems above, this paper proposes a method for generating complex texture features in images using random variation of pixels. With an annealing algorithm that can find an optimal solution in a large search space, the image is optimally optimized in terms of information entropy, pixel correlation, and value of x². Each iteration involves selecting one of 2⁵⁶³² combinations of DNA coding and operation. In comparison with current encryption algorithms based on optimization algorithms and DNA coding, this method is more secure and unbreakable.