journal article·2024-07-17Open access

A DWT-Based Approach with Gradient Analysis for Robust and Blind Medical Image Watermarking

Khaled Hebbache, Belal Khaldi, Oussama Aiadi, Ali Benziane

Applied Sciences· Volume 14· Issue 14

Abstract

The growing adoption of telemedicine necessitates robust security measures for medical images during transmission. This paper proposes a novel blind watermarking system for medical images that utilizes both image gradients and the Discrete Wavelet Transform (DWT). Image gradients, acting as spatial derivatives, provide a “topological map” of the image, aiding in the identification of areas susceptible to disruption. The DWT, with its multi-resolution analysis, offers a favorable balance between robustness and imperceptibility. The proposed method embeds the watermark within the low–low band (LL) of the DWT-decomposed image, specifically in 3 × 3 block regions selected based on gradient information. The mathematical relationships between the gradient’s direction and magnitude are employed to extract the corresponding blocks and their codes adequately. These codes are then XORed with the watermark and embedded into the chosen blocks using the least significant bit (LSB) technique. Extensive experimentation on a medical image dataset evaluates the system’s performance against some attacks like filtering, noise, and scaling. The results demonstrate the efficacy of the proposed approach in hiding information while ensuring the security and integrity of watermarked medical images.
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Research context

OpenAlex topics: Advanced Steganography and Watermarking Techniques · Digital Media Forensic Detection · Image and Signal Denoising Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Computer Science and Information Technologies, University of Kasdi Merbah, Ouargla 30000, Algeria

Laboratoire d’Intelligence Artificiel et des Technologies de l’Information (LINATI), Ouargla 30000, Algeria

Faculty of Sciences and Technology, University of Ziane Achour, Djelfa 17000, Algeria

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