Quantization Index Modulation Method Research Articles

Adaptive Video Watermarking against Scaling Attacks Based on Quantization Index Modulation

Video watermarking plays a vital role in protecting the video copyright. The quantization-based methods are widely used in the existing watermarking algorithms, owing to their low computational complexity and completely blind extraction. However, most of them work poorly in resisting scaling attacks, by which the quantization value may fall outside the original quantization interval. For addressing this issue, an adaptive quantization index modulation method is proposed. The property that is associated with the ratio of the DC coefficient before and after scaling the video resolution motivates us to select the DC coefficient as the quantization value and set the size of the quantization interval by the video resolution to maintain the synchronization between them before and after scaling. Moreover, a strategy taking advantage of the high decoding reliability of the QRCode is proposed to terminate the extraction in advance, and both the embedding and the extracting process are performed in the spatial domain, which all contribute to further enhance the execution efficiency. The experimental results show that our algorithm outperforms the state-of-the-art method in terms of imperceptibility, robustness, and computational cost.

Algorithm of error-free information embedding into the DCT domain of digital images based on the QIM method using adaptive masking of distortions

This paper proposes a new algorithm for hiding data in the frequency domain of digital images using the discrete cosine transform. This algorithm uses quantization index modulation (QIM) as the basic embedding operation. Frequency embedding is characterized by the problem of error appearance in a secret message arising directly at the embedding stage. The embedded message is distorted due to the loss of information when restoring integer pixel values from the frequency domain. This problem is significant if the integrity of the transmitted information is critical. For example, an insignificant distortion of an encrypted message leads to the impossibility of decrypting and, consequently, to the loss of all encrypted information. The proposed algorithm solves this problem via an iterative embedding procedure, which corrects the arising errors. Another distinctive feature of this algorithm is the adaptive correction of distortions of the frequency coefficients’ histogram. For this purpose, the embedding procedure adapts to the features of the image and masks the arising distortions. Computing experiments and comparison with the state-of-the-art demonstrate the effectiveness of our algorithm.

Quaternion Discrete Fourier Transform-Based Color Image Watermarking Method Using Quaternion QR Decomposition

In this paper, a new Quaternion Discrete Fourier Transform (QDFT)-based digital color image watermarking method is presented. In addition, the Quaternion QR (QQR) decomposition is applied in digital watermarking technology for the first time. First of all, the QDFT and QQR decomposition are performed on the host image, respectively, to acquire the scalar part of the quaternion matrix for watermark information embedding. After that, we divide the scalar part of the quaternion matrix generated by the QQR decomposition into blocks and calculate the entropy. The block with high entropy is selected to embed the watermark information. Then the watermark information is embedded into the extracted block using the quantization index modulation method. We conducted a large number of tests and experimental results indicate that the presented approach obtains excellent robustness against Scaling, Rotation, Median filtering, `Salt & Pepper' noise, and JPEG Compression. Compared with the existing methods, the presented method achieves better performance.

Audio Watermarking Combined with Compressive Sampling Based on QIM and DST-QR Techniques

Abuse is not only done to copy or distribute data but also to the digital copyright labels. There is a way to protect data by inserting or hiding a piece of certain information, namely a watermarking technique. In this paper, we propose audio watermarking with Quantization Index Modulation (QIM) method as an embedding process combined with Compressive Sampling (CS), Discrete Sine Transform (DST) and QR decomposition. Binary image is used as a watermark inserted in host audio. DST is used for transformation process from time domain to frequency domain, while QR is used to decompose onedimension matrix into two-dimension matrix. Meanwhile, CS is used to obtain the compressed watermark file which is done before the embedding process. QIM method is used to embed the watermark file to the audio host file. Simulation results indicated that the proposed audio watermarking technique has good robustness against some attacks such as Low Pass Filter (LPF), resampling and linear speed change. In addition, it provides good performance in terms of imperceptibility with Signal to Noise Ratio (SNR) > 20 dB and capacity C = 689 bps.

Color image watermarking using a discrete trinion Fourier transform

A discrete trinion Fourier transform (DTFT) is proposed and computation of the DTFT is derived from the discrete Fourier transform. A block-based color image watermarking scheme is designed based on the proposed DTFT. The watermark bits are embedded by modifying the DTFT coefficients of each block by means of the quantization index modulation method. Finally, assessment of this watermarking approach is performed in terms of watermark capacity, invisibility, and robustness. A comparison with a quaternion discrete Fourier transform is also provided. Experimental results show that the proposed method is not only more robust in most standard attack situations, but also has superior time efficiency.

New secure QIM-based information hiding algorithms

The paper proposes two information hiding algorithms for multimedia based on Quantization Index Modulation (QIM): IM-QIM and SIM-QIM. They are designed to prevent a statistical attack which is able to restore a secret key using the correlation between key bits and multimedia data samples. To obtain the required security, we use a correlation immune embedding function, which guarantees statistical independence between the watermarked data and the key. The proposed algorithms are described for the case of spatial embedding in images but the algorithms can also be used to hide information in any multimedia data source in spatio-temporal and spectral domains. The results of the experimental investigation have confirmed that the algorithms developed provide the required security against a statistical attack and also have shown that the algorithms do not introduce additional distortions compared with the conventional QIM method. However, the experiments have also shown that the new algorithms are less robust against additive noise and JPEG compression.

Método de ocultamiento de píxeles para esteganografía de imágenes en escala de gris sobre imágenes a color

El proceso de ocultar datos secretos dentro de una señal huésped se conoce como esteganografía; sus parámetros de diseño son la imperceptibilidad, la capacidad de ocultamiento y la calidad de los datos recuperados. En el caso de imágenes, uno de los métodos existentes basado en la modicación de los píxeles de la imagen huésped es el denominado BPHM (Block Pixel Hiding Method), el cual presenta una buena imperceptibilidad y alta capacidad de ocultamiento, pero no garantiza la calidad de la imagen secreta recuperada. Este artículo propone un método que mejora los resultados de BPHM basado en la selección de banda y un algoritmo de búsqueda global denominado IPHM (Improved Pixel Hiding Method). De acuerdo a las simulaciones realizadas, los resultados obtenidos con IPHM son mejores a los obtenidos con BPHM y son similares a uno de los métodos más populares en esteganografía de imágenes conocido como QIM (Quantization Index Modulation).

Steganography integrated into linear predictive coding for low bit-rate speech codec

The extensive use of Voice over IP (VoIP) applications makes low bit-rate speech stream a very suitable steganographic cover media. To incorporate steganography into low bit-rate speech codec, we propose a novel approach to embed information during linear predictive coding (LPC) process based on Matrix Embedding (ME). In the proposed method, a mapping table is constructed based on the criterion of minimum distance of Linear-Predictive-Coefficient-Vectors, and embedding position and template are selected according to a private key so as to choose the cover frames. The original speech data of the chosen frames are partially encoded to get the codewords for embedding and then the codewords that need to be modified for embedding are selected according to the secret bits and ME algorithm. The selected codeword will be changed into its best replacement codeword according to the mapping table. When embedding k (k > 1) bits into 2kź1 codewords, the embedding efficiency of our method is k times as that of LPC-based Quantization Index Modulation method. The performance of the proposed approach is evaluated in two aspects: distortion in speech quality introduced by embedding and security under steganalysis. The experimental results demonstrate that the proposed approach leads to a better performance with less speech distortion and better security.

Neighbor-index-division steganography based on QIM method for G.723.1 speech streams

Quantization index modulation (QIM) is a commonly used steganography method exploiting redundancy in codebook quantization procedure of signal encoding. The feasibility of steganography based on QIM depends on codebook division algorithm which mainly determines embedding capacity, latency and complexity of embedding and extracting algorithm. A novel neighbor-index-division (NID) codebook division method with a simple and more security implementation for G.723.1 speech streams is proposed. Differing from existing complementary neighbor vertices (CNV) algorithm, NID divides neighbor-indexed codewords into separated sub-codebooks (partitions) combined with a suitable stego coding strategy. Moreover, NID method makes multiple division (k sub-codebooks, k ≥ 3) for one single codebook possible, thus increases embedding capacity. To take full advantage of the partitions especially for odd-numbered division, multi-ary coding strategy is introduced in embedding and extracting procedures. Experimental results demonstrate that proposed method has almost the same distortion compared with CNV in binary division condition but a much easier implementation and introduces flexible multiple division methods which is more suitable for practical covert communication applications. Further, by applying a commonly used COV(1, 3, 2) stego coding strategy, NID is able to resist the state-of-art steganalysis towards QIM with a still practical embedding rate.

Object-oriented stereo-image digital watermarking

We present an object-oriented method for watermarking stereo images. Since stereo images are characterized by the perception of depth, the watermarking scheme we propose relies on the extraction of a depth map from the stereo pairs to embed the mark. The watermark embedding is performed in the wavelet domain using the quantization index modulation method. Experimental results show that the proposed method is a semifragile one that is robust toward JPEG and JPEG2000 compression and fragile with respect to other signal manipulations.

An overview of scalar quantization based data hiding methods

In Ref. [Costa, Writing on dirty paper, IEEE Trans. Inform. Theory 29 (1983) 439–441.], Costa presented a communications framework that provided useful insights into the study of data hiding. We present an alternate and equivalent framework with a more direct data hiding perspective. The difference between the two frameworks is in how channel dependent nature is reflected in optimal encoding and decoding operations. The connection between the suggested encoding/decoding scheme and practical embedding/detection techniques is examined. We analyze quantization based embedding/detection techniques in terms of the proposed framework based on three key aspects. The first aspect is the type of postprocessing utilized at the embedder (i.e. distortion compensation [Chen, Wornell, Preprocessed and postprocessed quantization index modulation methods for digital watermarking, in: Proceedings of SPIE: Security and Watermarking of Multimedia Contents II, vol. 3971, 2000, pp. 48–59; Eggers, Su, Girod, A blind watermarking scheme based on structured codebooks, IEE Colloq. Secure Images Image Authentication 4 (2001) 1–6.], thresholding [Ramkumar, Akansu, Self-noise suppression schemes for blind image steganography, in: Proceedings of SPIE International Workshop on Voice, Video and Data Communication, Multimedia Applications, vol. 3845, 1999.], Gaussian mapping [Perez-Gonzalez, Balado, Hernandez Martin, Performance analysis of existing and new methods for data hiding with known-host information in additive channels, IEEE Trans. Signal Process. 51(4) (2003) 960–980].). The second key aspect is the form of demodulation used at the extractor. The third is the criteria used to optimize the embedding/detection parameters. The embedding/detection techniques are compared in terms of probability of error, correlation, and mutual information (hiding rate) performance merits.

Quantization Index Modulation Methods for Digital Watermarking and Information Embedding of Multimedia

Copyright notification and enforcement, authentication, covert communication, and hybrid transmission applications such as digital audio broadcasting are examples of emerging multimedia applications for digital watermarking and information embedding methods, methods for embedding one signal (e.g., the digital watermark) within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient trade-offs among the three conflicting goals of maximizing information-embedding rate, minimizing distortion between the host signal and composite signal, and maximizing the robustness of the embedding. We present a class of embedding methods called quantization index modulation (QIM) that achieve provably good rate-distortion-robustness performance. These methods, and low-complexity realizations of them called dither modulation, are provably better than both previously proposed linear methods of spread spectrum and nonlinear methods of low-bit(s) modulation against square-error distortion-constrained intentional attacks. We also derive information-embedding capacities for the case of a colored Gaussian host signal and additive colored Gaussian noise attacks. These results imply an information embedding capacity of about 1/3 b/s of embedded digital rate for every Hertz of host signal bandwidth and every dB drop in received host signal quality. We show that QIM methods achieve performance within 1.6 dB of capacity, and we introduce a form of postprocessing we refer to as distortion compensation that, when combined with QIM, allows capacity to be achieved. In addition, we show that distortion-compensated QIM is an optimal embedding strategy against some important classes of intentional attacks as well. Finally, we report simulation results that demonstrate the performance of dither modulation realizations that can be implemented with only a few adders and scalar quantizers.