Hybrid Mode of Medical Image Watermarking To Enhance Robustness and Imperceptibility

Abstract

In Modern healthcare systems, diagnostic information of patients is managed digitally. Watermarking strategies plays a significant role to ensure the security, authenticity and management of biomedical images and related patient information. This paper explores different invisible Digital watermarking methods both in spatial and transform / frequency domain and then Hybrid method by combining two techniques to justify better results for medical images. Here, host image considered is a medical image and patient’s information is a watermark which is embedded into it. The embedded watermark is hidden in medical host image and its quality should not be degraded to avoid misdiagnosis by doctors. In this paper, LSB, SVD, DCT, DWT and Hybrid techniques (DWT+SVD) are implemented for embedding and extraction process of invisible medical image watermarking. The performance is evaluated based on PSNR as a measure of imperceptibility and CRC & SSIM as a check of robustness. The attacks introduced are cropping, rotating, and noise like Gaussian, Salt & Paper, Speckle and Poisson. Results reveal that DWT provides higher PSNR values but it is robust for few attacks only. On the other side, SVD provides consistent SSIM for all attacks, although PSNR values are less than that of DWT. Hence a hybrid technique is implemented by incorporating benefits of DWT and SVD both and achieved optimal values of PSNR as well as SSIM to provide better security to medical images by preserving the quality as well.

Advances in medical image watermarking: a state of the art review

“…It is a parameter that is used for the calculation of similarity between the original medical image and watermarked medical image [ 20 , 88 , 95 ]. The watermark should be embedded in the host medical image in a way that it (watermark) is not perceptible to the Human Visual System (HVS) and maintains the quality of the host image.…”

“…Imperceptivity or watermark invisibility is the measure of similarity between the cover medical image (CMI) and the Watermarked Medical Image (WMI). It is the measure for the level of invisibility of the watermark in WMI and can be calculated as Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM) [ 50 , 88 ].…”

“…Sharing of digital medical images over the cloud or internet is taking place in huge amounts resulting in increased active and passive attacks on this data. Manipulation, snooping, deletion, copying, and other unauthorized access to medical data have increased by a huge amount [ 7 , 8 , 59 , 60 , 83 , 88 , 96 ]. The variation in medical image data along with the patient’s confidential data may lead to adverse effects.…”