Image contrast enhancement is a prerequisite and plays a very important role in many image processing field like medical imaging, face recognition, computer-vision, and satellite imaging. In this paper we proposed reversible data hiding based Limited Dynamic Weighted Histogram Equalization techniques for Abnormal Tumor regions which improve the contrast, transmit the hidden secret information, preserve its brightness intensity and original appearance of the image. We have implemented Otsu’s method to segment the input image into two sub-histogram regions of interest (ROI) and non-region of interest; furthermore, the sub-histograms ROI region equalized independently without of over-enhancement and any loss of hidden and diagnostic data. Our proposed method is more efficient to precisely preserve the brightness of the image and extract the secret information with contrast image reversibly; besides, different classifiers are used to classify the brain cancer to check the performance of our proposed method.

中文翻译：

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基于 RDH 的动态加权直方图均衡用于安全传输和癌症预测

图像对比度增强是一个先决条件，在医学成像、人脸识别、计算机视觉和卫星成像等许多图像处理领域中发挥着非常重要的作用。在本文中，我们针对异常肿瘤区域提出了基于可逆数据隐藏的有限动态加权直方图均衡技术，该技术提高了对比度，传输了隐藏的秘密信息，保留了图像的亮度强度和原始外观。我们已经实现了 Otsu 的方法，将输入图像分割为两个子直方图感兴趣区域 (ROI) 和非感兴趣区域；此外，子直方图 ROI 区域独立均衡，没有过度增强和任何隐藏和诊断数据的丢失。我们提出的方法更有效地精确保留图像的亮度并可逆地提取对比度图像的秘密信息；此外，使用不同的分类器对脑癌进行分类，以检查我们提出的方法的性能。