Multilevel Reversible Data Hiding By Using Histogram Shifting And Dynamic Block Partition

In this dissertation,we study the pre-reserving space for data embedding that plays a vital role in maximum data embedding as they make available extra space for data embedding because low compression ratio cannot provide much space to control extra bits;consequently,as a result on a small block,partition region cannot accommodate enough data.As we know that on lower block level we can gain highest embedding capacity;however,especially on the smooth region and rough region based on dynamic partition play a significant role to find most optimal place to write information and sustain a high quality of the image with maximum embedding rate.We proposed a new technique for reversible data hiding based on the efficient compressed domain with multiple bit planes.We conducted a sequence of experiments to use block division scheme to appraise the result with different parameters and amended the probability of zero points in every block of the histogram.This scheme attained more embedding capacity and high-quality of stego-image.Experimental consequences effectively achieved the objective of high embedding capacity and sustaining the quality of the image.Furthermore,we extrapolate an innovative reversible data hiding technique that is for-mulated on histogram shifting by using multilayer localized n-bit truncation image(LBPTI),generated from the 8-bit plane by means of efficient lossless compression.After selecting the reference point from the block,the neighbor topmost points are used to attain the data embedding without modifying the peak point;in addition,the key information regarding peak point is not mandatory in extraction end to extract the secret information.In order to make the embedded cover-image similar to the histogram of original cover-image,we exploited the localization with efficient lossless compression on lower block level to increase the embedding capacity while controlling extra bit to expand additional embedding capacity on an optimum level besides sustaining the quality of cover-image.In preceding PVO-based schemes select the smooth region based on the noise level in the block as well as the distinct block size dramatically act the performance of EC.We discussed a novel Generalized PVO based reversible data hiding using Firefly Algorithm(GPVOFA).The sequence of minimum and maximum pixels value has used to embed the secret data while predicted into multiple pixels value for each block.The host image is divided into non-coinciding dynamic blocks size based on quadtree partition,and rough blocks are divided into larger size;moreover,providing more embedding capacity used small blocks size and optimal location in the block to write the information.Our proposed method becomes able to embed large data into a host image with low distortion.With rich experimental results also outperforms compare with other related preceding arts.Traditional reversible data hiding schemes only emphasis on increasing the embedding capacity and high PSNR ratio;however,traditional RDH schemes are unable to enhance the visual quality of low contrast-image after reversible data hiding procedure.We discussed the RDH based dynamic weighted histogram equalization techniques for abnormal tumor regions which improve the contrast,preserve its brightness intensity,decrease the number of distorted pixels,and the original appearance of the image.In segmentation,the input image is divided into two sub-histogram,a region of interest(ROI)and non-region of interest(Non-ROI);furthermore,the sub-histograms ROI region equalized independently without of over-enhancement,and any loss of diagnostic data.