In most of the digital steganography methods provided for natural digital images, the embedding of the confidential message is based on the minimisation of the defined distortion functions. It is often done based on choosing the most optimal criterion of distortion. Although the distortion functions are designed innovatively, steganography algorithms will be optimal. In such approaches, embedding interactions are often overlooked. Unlike usual images that have areas with a variety of tissue features, there are many smooth areas in medical images that will make the changes more visible if they are manipulated. Therefore, this study presents an adaptive approach that comes from the interactions between the changes made during the embedding algorithm to reduce the probability of recognising the message embedded in medical images and reducing the distortion caused by embedding in a discrete cosine transform space and based on the imperialist competitive algorithm for joint photographic experts group images, especially in medical images due to the importance of information steganography in them. The results obtained show the high efficiency of the proposed algorithm in comparison with the state‐of‐the‐art methods that are presented in this area.
In this article, due to the importance of embedding encrypted information in the image, a watermarking method is proposed based on local statistics in pixels. The advantages of the proposed method include its complete reversibility and very high security, which is due to the use of the quadtree concept, finding similar parts in the image, and embedding information in low‐energy and less significant pixels. This method is an alternative and simplifier of the quadtree method, dividing the image into identical non‐overlapping blocks and then choosing the block with less energy as more suitable for watermarking. Also, two criteria of mean‐squared‐error and peak signal‐to‐noise ratio (PSNR) have been calculated and the PSNR shows that image quality has not changed too much after hiding the information than the original image. It should be noted that since the proposed method is applied to black and white images, the result can be generalized to different color channels in the image, and color images have more visible capabilities in terms of cached memory than black and white images because they contain three dimensions of information.
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