A Novel Reversible Image Camouflaging Method Based on Lossless Matrix Transformation

Image encryption methods aim to transform a secret image into a noise-like, texture-like image. Since this behavior of the encrypted image indicates that it is encrypted, it provokes a large number of attacks. One of the most effective methods to counter this threat is to protect the information by transforming the original image into a new, meaningful image. The bottleneck of this approach is that the new image in which the information is embedded must have a high visual quality that is indistinguishable from the real image. Another critical requirement is obtaining the original image without loss. In this paper, we propose a reversible image camouflage method based on lossless matrix transformation and two-dimensional wavelet transformation. Random matrix perturbation is introduced and applied as an effective method for the lossless transformation of low-frequency or flat regions. The proposed method was applied to different datasets for performance analysis. The PSNR values of the plain/camouflage image pair are above 55 dB, and the SSIM values obtained by our method are very close to 0.9999 on these datasets. The experimental results demonstrate that the method’s performance is independent of the content of the plain/target image and of the fragment size. Furthermore, in cases where the target image is specifically chosen, PSNR values exceed 58 dB. Additionally, the efficacy of the method in generating camouflage images has been demonstrated through histogram analysis and performance analysis in the low- and high-frequency regions.