Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on the local complexity of a pixel is used to collect the PPEs to generate an ordered PPE sequence so that, smaller PPEs will be processed first for data embedding. By reversibly shifting the PPE histogram (PPEH) with optimized parameters, the pixels corresponding to the altered PPEH bins can be finally modified to carry the secret data. Experimental results have implied that the proposed method can benefit from the prediction procedure of the PEs, sorting technique as well as parameters selection, and therefore outperform some state-of-the-art works in terms of payload-distortion performance when applied to different images.Comment: There has no technical difference to previous versions, but rather some minor word corrections. A 2-page summary of this paper was accepted by ACM IH&MMSec'16 "Ongoing work session". My homepage: hzwu.github.i

High capacity data embedding schemes for digital media

High capacity image data hiding methods and robust high capacity digital audio watermarking algorithms are studied in this thesis. The main results of this work are the development of novel algorithms with state-of-the-art performance, high capacity and transparency for image data hiding and robustness, high capacity and low distortion for audio watermarking.En esta tesis se estudian y proponen diversos métodos de data hiding de imágenes y watermarking de audio de alta capacidad. Los principales resultados de este trabajo consisten en la publicación de varios algoritmos novedosos con rendimiento a la altura de los mejores métodos del estado del arte, alta capacidad y transparencia, en el caso de data hiding de imágenes, y robustez, alta capacidad y baja distorsión para el watermarking de audio.En aquesta tesi s'estudien i es proposen diversos mètodes de data hiding d'imatges i watermarking d'àudio d'alta capacitat. Els resultats principals d'aquest treball consisteixen en la publicació de diversos algorismes nous amb rendiment a l'alçada dels millors mètodes de l'estat de l'art, alta capacitat i transparència, en el cas de data hiding d'imatges, i robustesa, alta capacitat i baixa distorsió per al watermarking d'àudio.Societat de la informació i el coneixemen

A Brief Review of RIDH

The Reversible image data hiding (RIDH) is one of the novel approaches in the security field. In the highly sensitive domains like Medical, Military, Research labs, it is important to recover the cover image successfully, Hence, without applying the normal steganography, we can use RIDH to get the better result. Reversible data hiding has a advantage over image data hiding that it can give you double security surely

Very High Embedding Capacity Algorithm for Reversible Image Watermarking

Reversible image watermarking enables the embedding of copyright or useful information in a host image without any loss of information. Here a novel technique to improve the embedding capacity i.e. reversible watermarking using an adaptive prediction error expansion & pixel selection is proposed. This work is an improvement in conventional Prediction Error Expansion by adding two new techniques adaptive embedding & pixel selection. Instead of uniform embedding, here one or two bits of watermark are adaptively embed into the expandable pixels as per the regional complexity. Adaptive Prediction Error Expansion can obtain the embedded rate upto 1.3 bits per pixel as compared to the 1 BPP of conventional Prediction Error Expansion. Also an intermediate step of prediction error expansion is proposed to select relatively smooth pixels and ignore the rough ones. In other words, the rough pixels may remain unchanged, and only smooth pixels are expanded or shifted. Therefore compared with conventional Prediction Error Expansion, a more sharply distributed prediction error histogram is obtained i.e. , and a larger proportion of prediction-errors in the histogram are expanded to carry hidden data. So the amount of shifted pixels is diminished, which leads to a better image quality. With these improvements, this method performs better than conventional Prediction Error Expansion. It can embed larger payloads with less distortion (almost 30% greater than the conventional method). DOI: 10.17762/ijritcc2321-8169.150510

General Framework of Reversible Watermarking Based on Asymmetric Histogram Shifting of Prediction Error

This paper presents a general framework for the reversible watermarking based on asymmetric histogram shifting of prediction error, which is inspired by reversible watermarking of prediction error. Different from the conventional algorithms using single-prediction scheme to create symmetric histogram, the proposed method employs a multi-prediction scheme, which calculates multiple prediction values for the pixels. Then, the suitable value would be selected by two dual asymmetric selection functions to construct two asymmetric error histograms. Finally, the watermark is embedded in the two error histograms separately utilizing a complementary embedding strategy. The proposed framework provides a new perspective for the research of reversible watermarking, which brings about many benefits for the information security

Data Security using Reversible Data Hiding with Optimal Value Transfer

In this paper a novel reversible data hiding algorithm is used which can recover image without any distortion. This algorithm uses zero or minimum points of an image and modifies the pixel. It is proved experimentally that the peak signal to noise ratio of the marked image generated by this method and the original image is guaranteed to be above 48 dB this lower bound of peak signal to noise ratio is much higher than all reversible data hiding technique present in the literature. Execution time of proposed system is short. The algorithm has been successfully applied to all types of images