用于对比度增强的医学图像可逆信息隐藏算法

用于医学图像对比度增强的可逆数据隐藏不仅能够利用可逆嵌入完成患者信息的存储，还可以实现对比度增强改善图像质量，在一定程度上帮助医生对患者疾病进行正确诊断.提出了一种新的用于医学图像对比度增强的可逆信息隐藏算法.该方法采用超像素分割医学图像，着重强调医学诊断的感兴趣区域的可逆嵌入与对比度增强.同时，将嵌入区域分为多个像素块，根据其统计特性有选择性地逐块修改.每个像素块采用经典的直方图修改方式，以直方图均衡化为优化目标，一次完成多个嵌入点的修改，从而减少在对比度增强过程中的嵌入失真.实验结果表明，与主流方法相比，该方法在兼顾可逆性能的同时，能进一步增强医学图像感兴趣区域的对比度，提高图像的视觉质量.

Algorithm of Medical Image Reversible Data Hiding for Contrast Enhancement

Reversible data hiding for medical image contrast enhancement can not only store patient information imperceptibly, but also improve image contrast quality to facilitate the accurate diagnosis in the remote medical affairs. In this paper, a new reversible data hiding algorithm for medical image contrast enhancement is proposed. The medical image is segmented by the superpixel algorithm, and then the modifications on the region of the interest (ROI) of the image are optimized. Since the image is divided into blocks, the embedded regions can be selectively modified block by block according to their statistical characteristics. Subsequently, the modification of each pixel block applies the classical histogram modification manner, and embeds the payload into multiple embedding points at one time. We take the histogram equalization as the optimization goal, and then reduce the embedding distortion in the process of contrast enhancement. Experimental results show that when compared with the state-of-the-art methods, the proposed method is reversible and can improve the visual quality of medical images in terms of contrast enhancement.