A high-capacity reversible data hiding with contrast enhancement and brightness preservation for medical images

被引：0

作者：

Gandhi S. ^{[1
]}

Kumar R. ^{[1
]}

机构：

[1] Department of Computer Science and Engineering, Delhi Technological University, Delhi

来源：

Multimedia Tools and Applications | 2025年 / 84卷 / 8期

关键词：

Contrast enhancement; Embedding capacity; Image segmentation; Medical images; Pre-processing; Reversible data hiding;

D O I：

10.1007/s11042-024-18934-1

中图分类号：

学科分类号：

摘要：

The healthcare industry has witnessed an increase in the use of cloud storage, resulting in a significant demand for safeguarding medical records from potential attackers. In response to this challenge, reversible data hiding (RDH) has emerged as a lifesaver. The RDH ensures the concealment of private and confidential data with minimal loss to the cover image while offering opportunities for image enhancement. This paper introduces a new RDH method with contrast enhancement for medical images. The method aims to provide high embedding capacity (EC) while preserving brightness. To achieve this, the proposed method initially segments cover images into regions of interest (ROI) and non-regions of interest (NROI) and employs different embedding strategies based on the characteristics of each region, thereby enhancing embedding performance. Furthermore, a novel pre-processing technique is introduced for processing ROI pixels. This technique re-organizes and creates empty bins to provide enlarged EC with less distortion by capitalizing on the unique properties of medical images. Additionally, the proposed method embeds secret data in the NROI to further increase the EC. Experimental results show that the proposed method effectively preserves brightness (with 0.99 Relative Mean Brightness Error) while providing higher EC, exceeding the best-known methods by 20%. Furthermore, the method enhances contrast with minimal distortion in the output images. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

引用

页码：5239 / 5264

页数：25

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