RDH-based dynamic weighted histogram equalization using for secure transmission and cancer prediction

Abstract

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.