Quantized DCT Coefficients Research Articles

Reliable JPEG steganalysis based on multi-directional correlations

With the wide application of JPEG images, JPEG steganography attracts more and more researchers, and accordingly, the detection of JPEG steganography becomes also important. There exist some blind JPEG steganalysis methods, while most of them are either unreliable or time-consuming. This paper presents a reliable and efficient steganalysis scheme to detect the popular JPEG steganography algorithms. First, a novel kind of transition probability matrix is constructed to describe correlations of the quantized DCT coefficients in multi-directions. Then, by merging two different calibrations, a 96-dimensional feature vector is extracted. Additionally, the SVM (Support Vector Machine) is trained to build the steganalyzer. Finally, the proposed feature is evaluated, and a series of experiments are performed on 4 kinds of typical steganography in different embedding ratios, showing that for these steganography algorithms, the new method is more reliable than the best effective blind detection methods existed.

JPEG Images Authentication with Discrimination of Tampers on the Image Content or Watermark

The existing compressed-domain fragile watermarking scheme cannot effectively discriminate tampers on the image contents or the embedded watermark or both tampered by attackers; hence, a novel compressed-domain fragile watermarking scheme with the discrimination of tampers on the image content or watermark based on a chaotic system is proposed in this paper. The quantized discrete cosine transform (DCT) coefficients of seven most significant bits (MSBs) after decoding are mapped to the initial values of the chaotic system, and then a content-based fragile watermark is generated by chaotic motion. After watermark permutation by the chaotic sequence, the operations of embedding and extracting the improved security watermark are all in the compressed domain. During authentication, the proposed method is able to detect the tampered location and discriminates tampers on the image content or watermark from the distribution density of nonzero elements in the tamper detection matrix. The quantized DCT coefficients after decoding are used directly for watermark embedding, which avoids the quantization effect on the detection of watermarks. Therefore, the proposed algorithm is very suitable for the JPEG image authentication. Furthermore, thanks to the high sensitivity to initial values and the good randomness of the chaotic system, the very accurate localization is not only realized for the malicious tampers to JPEG images, but also indicates whether the modification made to the watermarked image is on the image contents or the embedded watermark or both. Simulation results show the abilities of tamper discrimination and tamper localization of this technique.

Adaptive Method for Early Detecting Zero Quantized DCT Coefficients in H.264/AVC Video Encoding

In H.264/AVC video encoding, zero quantized discrete cosine transform (DCT) coefficients are quite common in low bit-rate video application. The computations of DCT and quantization can be remarkably reduced if zero quantized DCT coefficients are detected prior to DCT and quantization. Many methods have been applied to early detect most zero quantized DCT coefficients. But the detection ratios of zero quantized DCT coefficients need to be improved when quantization parameter (QP) is small. We present an adaptive method to detect zero quantized DCT coefficients. When QP exceeds a certain value, a new threshold is derived to efficiently detect the all-zero blocks (AZBs) without any video degradation. Otherwise, a concept of fourteen-zeros block (FZB), which means only two coefficients are non-zero in 16 DCT coefficients of a 4 times 4 block, is proposed. An innovative method to process FZBs is proposed to reduce the redundant computations. Experimental results show that the proposed adaptive method achieves approximately 8%-20% computational savings, compared with that of the existing methods.

Audio-Video synchronization coding approach based on H.264/AVC

In this paper, we proposed a novel audio video synchronization compression approach based on H.264/AVC, which is audio is embedded into quantized DCT coefficients of video in the encoder utilizing the parity properties of coefficients, then audio and video signals are compressed simultaneously. Different from the traditional methods, the proposed approach realizes the synchronization between video and audio in the coding layer. We've verified the synchronization processing method based on H.264/AVC using JM Model and experimental results show that this method does not increase the amount of data, and audio signal can be extracted without distortion. At the same time the algorithm has little effect on the quality of video.

Prediction of Zero Quantized DCT Coefficients in H.264/AVC Using Hadamard Transformed Information

This paper presents an efficient approach for detecting zero quantized discrete cosine transform (ZQDCT) coefficients using the sum of absolute transformed difference (SATD). Previously, all the ZQDCT prediction approaches employ the sum of absolute difference (SAD) available ahead of DCT and quantization (Q) for early detection. However, when the Hadamard transform is enabled for H.264/AVC encoding, only the SATD instead of SAD is available before DCT and Q, and all the prediction approaches can not be directly applied. To solve this problem, the Gaussian distribution is applied to study the integer 4x4 DCT coefficients in H.264/AVC and hence an adaptive scheme with multiple thresholds against SATD is derived to realize different types of DCT and Q implementations. In addition, another two SATD based sufficient conditions are proposed for early detecting zero quantized DC coefficients for the luma components encoded with the intra 16 times 16 mode and the chroma components. The experimental results demonstrate that the proposed approach can greatly reduce the DCT and Q computations and obtain almost the same rate-distortion performance as the original encoder.

Reversible Steganographic Method with High Payload for JPEG Images

This paper presents a lossless steganography method based on the multiple-base notation approach for JPEG images. Embedding a large amount of secret data in a JPEG-compressed image is a challenge since modifying the quantized DCT coefficients may cause serious image distortion. We propose two main strategies to deal with this problem: (1) we embed the secret values in the middle-frequency of the quantized DCT coefficients, and (2) we limit the number of nonzero values of the quantized DCT coefficients that participate in the embedding process. We also investigated the effect of modifying the standard quantization table. The experimental results show that the proposed method can embed twice as much secret data as the irreversible embedding method of Iwata et al. under the same number of embedded sets. The results also demonstrate how three important factors: (1) the quantization table, (2) the number of selected nonzero quantized DCT coefficients, and (3) the number of selected sets, influence the image quality and embedding capacity.

Efficient Scalable DCT Block-Based Image Coder with Compression of Signs of DCT Coefficients

This paper presents an efficient DCT based method for image compression. The method uses a sophisticated bit-plane coding of quantized DCT coefficients and provides both spatial and quality/speed scalability. A fast post-filtering aimed for deblocking and facilitation of Region of Interest (ROI) coding is also described. Utilizing the coding of signs of DCT coefficients further improves coding efficiency of the proposed coder. The coder can be used for lossy image compression as well as to further lossless compression of already compressed JPEG images whereas its performance is close to that one of JPEG2000.

Support Vector Machine (SVM) based compression artifact‐reduction technique

Abstract— A compression artifact‐reduction algorithm based on support vector regression is proposed. The algorithm belongs to a broad family of standard reconstruction methods, but a standardization model is determined from a set of training samples of original images and the corresponding noise‐corrupted version. As opposed to artifact‐reduction methods specific to each type of compression artifact (e.g., blocking, ringing, etc.), we treat such artifacts as a manifestation of the same problem, which is the quantization of DCT coefficients. In the testing step, the algorithm tries to undo the effect of quantization by using the relationship between the original and artifact‐corrupted image, determined during the training step. Experimental results exhibit significant reduction in all types of compression artifacts.

Hybrid Model to Detect Zero Quantized DCT Coefficients in H.264

In H.264 coding, there are a large number of discrete cosine transform (DCT) coefficients of the prediction residue which are quantized to zeros. Therefore, it is desired to design a method which can early detect zero quantized DCT coefficients (ZQDCT) before implementing DCT and quantization (Q) and thus reduce redundant computations for H.264 coding. To achieve this, a hybrid model is proposed in this paper in order to predict ZQDCT coefficients. First, the Gaussian distribution is applied to study the integer DCT coefficients in H.264 and hence an adaptive scheme with multiple thresholds is derived to realize different types of DCT and Q implementations. Then the adaptive scheme is further optimized by considering a more efficient condition to sufficiently detect all-zero DCT blocks. As a result, a hybrid model is developed. Compared with other methods in the literature, the proposed hybrid model is able to detect more ZQDCT coefficients and hence reduce more computations for H.264 encoding. It is shown by experimental results that the proposed hybrid model can achieve the best performance in reducing computations and obtain almost the same rate-distortion (R-D) performance as the original encoder in the H.264 reference software JM9.5

Locating Edges and Removing Ringing Artifacts in JPEG Images by Frequency-Domain Analysis

We present a method of locating edges in JPEG-coded images which operates in frequency space on the DCT coefficients. Applied to the quantized DCT coefficients of a block containing a straight edge, the method yields an equation for the edge in a fraction of the operations needed to dequantize and transform the coefficents to pixel values. As a sample application of this method, we present a technique for alleviating ringing artifacts in JPEG-coded images.

A steganographic method based upon JPEG and particle swarm optimization algorithm

In this paper, a novel steganographic method, based on JPEG and Particle Swarm Optimization algorithm (PSO), is proposed. In order to improve the quality of stego-images, an optimal substitution matrix for transforming the secret messages is first derived by means of the PSO algorithm. The standard JPEG quantization table is also modified to contain more secret messages. The transformed messages are then hidden in the DC-to-middle frequency components of the quantized DCT coefficients of the cover-image. Finally, a JPEG file with secret messages is generated through JPEG entropy coding. We compare our algorithm with Chang et al.’s JPEG-based steganographic algorithm. The experimental results show that our proposed method has larger message capacity and better image quality than Chang et al.’s. In addition, our method also has a high security level.

High-Quality DCT-Based Image Compression Using Partition Schemes

This letter presents an advanced discrete cosine transform (DCT)-based image compression method that combines advantages of several approaches. First, an image is divided into blocks of different sizes by a rate-distortion-based modified horizontal-vertical partition scheme. Statistical redundancy of quantized DCT coefficients of each image block is reduced by a bit-plane dynamical arithmetical coding with a sophisticated context modeling. Finally, a post-filtering removes blocking artifacts in decompressed images. The proposed method provides significantly better compression than JPEG and other DCT-based techniques. Moreover, it outperforms JPEG2000 and other wavelet-based image coders

A DCT-based Mod4 steganographic method

This paper presents a novel Mod4 steganographic method in discrete cosine transform (DCT) domain. Mod4 is a blind steganographic method. A group of 2 × 2 spatially adjacent quantized DCT coefficients (GQC) is selected as the valid message carrier. The modulus 4 arithmetic operation is then applied to the valid GQC to embed a pair of bits. When modification is required for data embedding, the shortest route modification scheme is applied to reduce distortion as compared to the ordinary direct modification scheme. Mod4 is capable in embedding information into both uncompressed and JPEG-compressed image. To compare Mod4 with other existing methods, carrier capacity, stego image quality, and results of blind steganalysis for 500 various images are shown. Visual comparison of three additional metrics is also presented to show the relative performance of Mod4 among other existing methods.

Efficient predictive model of zero quantized DCT coefficients for fast video encoding

Discrete cosine transform (DCT), quantization (Q), inverse quantization (IQ) and inverse DCT (IDCT) are the building blocks in video coding standards adopted by ITU-T and MEPG. Under these standards, a lot of computations are required to perform the DCT, Q, IQ and IDCT operations. With this concern, a novel statistical model based on Gaussian distribution is proposed to predict zero quantized DCT (ZQDCT) coefficients in order to reduce the computational complexity of video encoding. Compared with other predictive models in the literature, the proposed model can detect more ZQDCT coefficients. Simulation results demonstrate that the proposed statistical model is superior to others in terms of speeding up video encoders. Moreover, a hybrid model is derived based on the proposed statistical model and mathematical analysis of individual DCT coefficients to further improve the encoding efficiency.

Efficient prediction algorithm of integer DCT coefficients for H.264/AVC optimization

This paper presents a novel efficient prediction algorithm to reduce redundant discrete cosine transform (DCT) and quantization computations for H.264 encoding optimization. A theoretical analysis is performed to study the sufficient condition for DCT coefficients to be quantized to zeros. As a result, three sufficient conditions corresponding to three types of transform and quantization methods in H.264 are proposed. Compared with other algorithms in the literature, the proposed algorithm derives more precise and efficient conditions to predict zero quantized DCT coefficients. Both the theoretical analysis and experimental results demonstrate that the proposed algorithm is superior to other algorithms in terms of the computational complexity reduction, encoded video quality, false acceptance rate, and false rejection rate.

Efficient Motion Vector Composition Algorithm by Activity Measurement for Downscaled Video Transcoder

When the frame size is downscaled for video transcoding, the new motion vector (MV) must be computed. This paper presents an algorithm to utilize the activity measurement by DC value and the number of non-zero quantized DCT coefficients in the residual macroblock to compose the motion vector. It can reduce the complexity for motion estimation and improve the performance of the spatial domain video transcoder.

A method of estimating coding PSNR using quantized DCT coefficients

A new method of estimating coding peak signal-to-noise ratio (PSNR) without the use of reference signals is presented. Although PSNR is commonly used as a measure of the picture degradation of digitally coded video, the calculation requires source signals as a reference.Therefore, the usage of PSNR is restricted to particular applications or systems. The proposed method enables PSNR estimation based on the probability density functions of quantized discrete cosine transform (DCT) coefficients extracted from an MPEG-2 bit stream. We experimented with MPEG-2 video coding bit streams under varying quantization scheme and evaluate a new method with comparing estimated PSNRs with actual PSNRs. Experimental results indicate that the determination coefficients are higher than 0.9 This method can apply to both SDTV and HDTV, and can evaluate PSNR of every frame coded by different picture types.

Shared key encryption of jpeg color images

Several methods have been proposed for encrypting images by shared key encryption mechanisms since the work of Naor and Shamir. All the existing techniques are applicable to primarily non-compressed images in either monochrome or color domains. However, most imaging applications including digital photography, archiving, and Internet communications nowadays use images in the JPEG compressed format. Application of the existing shared key cryptographic schemes for these images requires conversion back into spatial domain. In this paper we propose a shared key algorithm that works directly in the JPEG domain, thus enabling shared key image encryption for a variety of applications. The scheme directly works on the quantized DCT coefficients and the resulting noise-like shares are also stored in the JPEG format. The decryption process is lossless preserving the original JPEG data. The experiments indicate that each share image is approximately the same size as the original JPEG image retaining the storage advantage provided by JPEG compression standard. Three extensions, one to improve the random appearance of the generated shares, another to obtain shares with asymmetric file sizes, and the third to generalize the scheme for n>2 share cases, are described as well.

High-performance JPEG steganography using quantization index modulation in DCT domain

This paper presents two JPEG steganographic methods using quantization index modulation (QIM) in the discrete cosine transform (DCT) domain. The two methods approximately preserve the histogram of quantized DCT coefficients, aiming at secure JPEG steganography against histogram-based attacks. In comparison with F5 as a representative JPEG steganography, the proposed methods show high performance with regard to embedding rate, PSNR of stego image, and particularly histogram preservation.

A fragile watermark error detection scheme for wireless video communications

In video communications over error-prone channels, compressed video streams are extremely sensitive to bit errors. Often random and burst bit errors impede correct decoding of parts of a received bitstream. Video decoders normally utilize error concealment techniques to repair a damaged decoded frame, but the effectiveness of these error concealment schemes relies heavily on correctly locating errors in the bitstream. In this paper, we propose a fragile watermark-based error detection and localization scheme called "force even watermarking (FEW)". A fragile watermark is forced onto quantized DCT coefficients at the encoder. If at the decoder side the watermark is no longer intact, errors exist in the bitstream associated with a particular macro-block (MB). Thanks to the watermark, bitstream errors can accurately be located at MB level, which facilitates proper error concealment. This paper describes the algorithm, model and analysis of the watermarking procedure. Our simulation results show that compared to the syntax-based error detection schemes, the proposed FEW scheme significantly improves the error detection capabilities of the video decoder, while the peak signal-to-noise ratio loss and additional computational costs due to watermark embedding and extraction are small.