Noise immunity algorithm for embedding a digital watermark in medical images

Abstract

When storing and transferring printed medical materials, such as tomograms or radiographs, there is a need to protect additional information from unauthorized access. This information includes personal data of the patient and a summary of the medical history, and it can be added to the medical image (container) in the form of a watermark. Existing algorithms for embedding digital watermarks (DWM) in graphic objects distort the initial characteristics of the container image, which in the case of medical images can lead to a misdiagnosis. This study aimed to develop a distortion- and noise-resistant algorithm for embedding the DWM in the spatial domain of a medical image intended for storage on paper (as a printout). The article initially considered the possibilities of using the method of modifying the least significant bits of image pixel brightness or the LSB algorithm. Mathematical modeling in Matlab showed that the maximum brightness of the DWM guaranteeing its invisibility cannot exceed 2% of the maximum brightness of the container image for monochrome images, and 6% for color images. The maximum value of the white noise dispersion, at which it is possible to single out a DWM with a correlation coefficient of at least 0.9 was 0.0001. We prorose a new noise immunе algorithm (NIA) for embedding the DWM in the subpixels of the main image, which, after extracting the DWM, are not used to build the container image. In the absence of noise, there are no distortions of the original medical image whatsoever. The essence of the NIA is as follows. The size of the original image in the form of a two-dimensional array is quadrupled by adding a subpixel in each row and column with a brightness equal to the average arithmetic brightness of neighboring pixels. A DWM with the same size as the original image is added to the resulting subpixels. Matlab modeling showed that the DWM would remain invisible at a relative brightness of approximately 5% for monochrome container images and 15% for color images. For the NIA algorithm, the maximum value of the white noise dispersion to obtain a correlation coefficient of 0.9 is 0.005, which means that the noise immunity of the proposed method is significantly higher than that of the LSB-based algorithm.