Adaptive Reversible Visible Watermarking Based on Total Variation for BTC-Compressed Images

Few previous Reversible Visible Watermarking(RVW)schemes have both good transparency and watermark visibility.An adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding(BTC)compressed domain,called TVB-RVW is proposed in this paper.A new mean image estimation method for BTC-compressed images is first developed with the help of Total Variation.Then,a visual perception factor computation model is devised by fusing texture and luminance characteristics.An adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC domain.Moreover,a lossless embedding method of the encrypted visible watermark is exploited to deter illegal watermark removal.The visible watermark can be removed since the visual perception factor and the estimated mean image remain unchanged before and after watermark embedding.Extensive experiments validate the superiority of the proposed algorithm over previous RVW schemes in BTC in terms of the visual quality of watermarked images and watermark visibility,and it can achieve a good balance between transparency and watermark visibility.

A HIGH-PERFORMANCE VLSI ARCHITECTURE OF EBCOT BLOCK CODING IN JPEG2000

The paper presents a new architecture composed of bit plane-parallel coder for Embedded Block Coding with Optimized Truncation (EBCOT) entropy encoder used in JPEG2000. In the architecture, the coding information of each bit plane can be obtained simultaneously and processed parallel. Compared with other architectures, it has advantages of high parallelism, and no waste clock cycles for a single point. The experimental results show that it reduces the processing time about 86% than that of bit plane sequential scheme. A Field Programmable Gate Array (FPGA) prototype chip is designed and simulation results show that it can process 512×512 gray-scaled images with more than 30 frames per second at 52MHz.

Fractal Block Coding:A New Method

Fractal image compression is a completely new method to compress images by searching and exploiting the self similarity of the whole image . Fractal Block Coding (FBC) is a practicable fractal coding scheme with annoying slow encoding speed . In this paper, we classify the image blocks by Classified Vector Quantization (CVQ) technique and present an Adaptive Block Truncation Coding (ABTC) scheme to process the midrange blocks in the image. By this method , we reduce the encoding time to one forty fifth comparing to ordinary FBC method with little change in compression ratio and a little decreased coded image quality.

Data Hiding in AMBTC Images Using Selective XOR Hiding Scheme

Nowadays since the Internet is ubiquitous,the frequency of data transfer through the public network is increasing.Hiding secure data in these transmitted data has emerged broad security issue,such as authentication and copyright protection.On the other hand,considering the transmission efficiency issue,image transmission usually involves image compression in Internet-based applications.To address both issues,this paper presents a data hiding scheme for the image compression method called absolute moment block truncation coding(AMBTC).First,an image is divided into nonoverlapping blocks through AMBTC compression,the blocks are classified four types,namely smooth,semi-smooth,semi-complex,and complex.The secret data are embedded into the smooth blocks by using a simple replacement strategy.The proposed method respectively embeds nine bits(and five bits)of secret data into the bitmap of the semi-smooth blocks(and semicomplex blocks)through the exclusive-or(XOR)operation.The secret data are embedded into the complex blocks by using a hidden function.After the embedding phase,the direct binary search(DBS)method is performed to improve the image qualitywithout damaging the secret data.The experimental results demonstrate that the proposed method yields higher quality and hiding capacity than other reference methods.

Single bitmap block truncation coding of color images using hill climbing algorithm

In order to generate an efficient common bitmap in single bitmap block truncation coding(SBBTC)of color images,an improved SBBTC scheme based on weighted plane(W-plane)method and hill climbing algorithm is proposed.Firstly,the incoming color image is partitioned into non-overlapping blocks and each block is encoded using the W-plane method to get an initial common bitmap and quantization values.Then,the hill climbing algorithm is applied to optimize an initial common bitmap and generate a near-optimized common bitmap.Finally,the quantization values are recalculated by the near-optimized common bitmap and the considered color image is reconstructed block by block through the common bitmap and the new quantization values.Since the processing of each image block in SBBTC is independent and identical,parallel computing is applied to reduce the time consumption of this scheme.The simulation results show that the proposed scheme has better visual quality and time consumption than those of the reference SBBTC schemes.