Reversible Data Hiding Scheme with High Embedding Capacity Using Semi-Indicator-Free Strategy

A novel reversible data-hiding scheme is proposed to embed secret data into a side-matched-vector-quantization- (SMVQ-) compressed image and achieve lossless reconstruction of a vector-quantization- (VQ-) compressed image. The rather random distributed histogram of a VQ-compressed image can be relocated to locations close to zero by SMVQ prediction. With this strategy, fewer bits can be utilized to encode SMVQ indices with very small values. Moreover, no indicator is required to encode these indices, which yields extrahiding space to hide secret data. Hence, high embedding capacity and low bit rate scenarios are deposited. More specifically, in terms of the embedding rate, the bit rate, and the embedding capacity, experimental results show that the performance of the proposed scheme is superior to those of the former data hiding schemes for VQ-based, VQ/SMVQ-based, and search-order-coding- (SOC-) based compressed images

Nested turbo codes for the costa problem

Driven by applications in data-hiding, MIMO broadcast channel coding, precoding for interference cancellation, and transmitter cooperation in wireless networks, Costa coding has lately become a very active research area. In this paper, we first offer code design guidelines in terms of source- channel coding for algebraic binning. We then address practical code design based on nested lattice codes and propose nested turbo codes using turbo-like trellis-coded quantization (TCQ) for source coding and turbo trellis-coded modulation (TTCM) for channel coding. Compared to TCQ, turbo-like TCQ offers structural similarity between the source and channel coding components, leading to more efficient nesting with TTCM and better source coding performance. Due to the difference in effective dimensionality between turbo-like TCQ and TTCM, there is a performance tradeoff between these two components when they are nested together, meaning that the performance of turbo-like TCQ worsens as the TTCM code becomes stronger and vice versa. Optimization of this performance tradeoff leads to our code design that outperforms existing TCQ/TCM and TCQ/TTCM constructions and exhibits a gap of 0.94, 1.42 and 2.65 dB to the Costa capacity at 2.0, 1.0, and 0.5 bits/sample, respectively

Compression Technique Using DCT & Fractal Compression: A Survey

Steganography differs from digital watermarking because both the information and the very existence of the information are hidden. In the beginning, the fractal image compression method is used to compress the secret image, and then we encrypt this compressed data by DES.The Existing Steganographic approaches are unable to handle the Subterfuge attack i.e, they cannot deal with the opponents not only detects a message ,but also render it useless, or even worse, modify it to opponent favor. The advantage of BCBS is the decoding can be operated without access to the cover image and it also detects if the message has been tampered without using any extra error correction. To improve the imperceptibility of the BCBS, DCT is used in combination to transfer stego-image from spatial domain to the frequency domain. The hiding capacity of the information is improved by introducing Fractal Compression and the security is enhanced using by encrypting stego-image using DES.  Copyright © www.iiste.org Keywords: Steganography, data hiding, fractal image compression, DCT

Weighted universal image compression

We describe a general coding strategy leading to a family of universal image compression systems designed to give good performance in applications where the statistics of the source to be compressed are not available at design time or vary over time or space. The basic approach considered uses a two-stage structure in which the single source code of traditional image compression systems is replaced with a family of codes designed to cover a large class of possible sources. To illustrate this approach, we consider the optimal design and use of two-stage codes containing collections of vector quantizers (weighted universal vector quantization), bit allocations for JPEG-style coding (weighted universal bit allocation), and transform codes (weighted universal transform coding). Further, we demonstrate the benefits to be gained from the inclusion of perceptual distortion measures and optimal parsing. The strategy yields two-stage codes that significantly outperform their single-stage predecessors. On a sequence of medical images, weighted universal vector quantization outperforms entropy coded vector quantization by over 9 dB. On the same data sequence, weighted universal bit allocation outperforms a JPEG-style code by over 2.5 dB. On a collection of mixed test and image data, weighted universal transform coding outperforms a single, data-optimized transform code (which gives performance almost identical to that of JPEG) by over 6 dB

A User Oriented Image Retrieval System using Halftoning BBTC

The objective of this paper is to develop a system for content based image retrieval (CBIR) by accomplishing the benefits of low complexity Ordered Dither Block Truncation Coding based on half toning technique for the generation of image content descriptor. In the encoding step ODBTC compresses an image block into corresponding quantizes and bitmap image. Two image features are proposed to index an image namely co-occurrence features and bitmap patterns which are generated using ODBTC encoded data streams without performing the decoding process. The CCF and BPF of an image are simply derived from the two quantizes and bitmap respectively by including visual codebooks. The proposed system based on block truncation coding image retrieval method is not only convenient for an image compression but it also satisfy the demands of users by offering effective descriptor to index images in CBIR system

A fast compression-based similarity measure with applications to content-based image retrieval

Compression-based similarity measures are effectively employed in applications on diverse data types with a basically parameter-free approach. Nevertheless, there are problems in applying these techniques to medium-to-large datasets which have been seldom addressed. This paper proposes a similarity measure based on compression with dictionaries, the Fast Compression Distance (FCD), which reduces the complexity of these methods, without degradations in performance. On its basis a content-based color image retrieval system is defined, which can be compared to state-of-the-art methods based on invariant color features. Through the FCD a better understanding of compression-based techniques is achieved, by performing experiments on datasets which are larger than the ones analyzed so far in literature

BER Performance of Audio Watermarking Using Spread Spectrum Technique

AbstractSending the private data is always one of the fundamental problems in the communication systems. Therefore, information hiding was presented to protect the data. The evolutionary process has been continued until the watermarking as a new technique was generated to promote the copyright marking. Watermarking is trying to embed the private data such as text or numbers as a guest signal in the host signal with minimal effect on it. Audio watermarking was introduced as a one of watermarking techniques against the attackers and hackers that were raised on social networks.This paper presents an audio watermark algorithm with a blind detection which is based on a spread spectrum (SS) technique. A series of simulations were done on the proposed algorithm to estimate the Bit Error Rate (BER) for various values of signal-to-watermarking ratio (SWR) and bit rate. The simulationresults show that by decreasing the SWR ratio, the BER ratio is reduced to less than 10−3