DWT Algorithm for Macro & Micro Block based Multiple Histogram Shifting for Video Data Hiding

With the help of video compression and compressive sensing technology, this study demonstrates how to conceal data. Video data was concealed using a linear sensing technique for greater quality. By reducing changes across pixels to obtain discrete micro-block features while keeping their statistical properties, micro-block residuals can be assessed using CS. In order to create many histograms, micro blocks with related features are grouped together using CS. The seamless integration of data into video is the project’s main objective. The picture quality ratio and PSNR rate of the image are improved using this method. This method uses a micro-block-based approach to increase PSNR and improve security. In order to eliminate shifting distortions, data embedding is used on each of these histograms to extend the outermost bins while maintaining the size of the inner bins. Numerous RDH strategies based on multiple HS (MHS) based on spatial correlations of multimedia are offered to protect copyright, in which several histograms are constructed using some strict criteria. Compared to photographs, video has more three-dimensional and temporal linkages, and it’s simple to obtain histograms with greater clarity. Reduced embedding distortions enable lossless restoration of the cover thanks to the reversible data hiding (RDH) technology. Histogram shifting is one RDH strategy that is widely employed (HS).