Recently, among various data hiding techniques, a new subset, lossless data hiding, has received increasing interest. Most of the existing lossless data hiding algorithms are, however, fragile in the sense that the hidden data cannot be extracted out correctly after compression or other incidental alteration has been applied to the stego-image. The only existing semi-fragile (referred to as robust in this paper) lossless data hiding technique, which is robust against high-quality JPEG compression, is based on modulo-256 addition to achieve losslessness. In this paper, we first point out that this technique has suffered from the annoying salt-and-pepper noise caused by using modulo-256 addition to prevent overflow/underflow. We then propose a novel robust lossless data hiding technique, which does not generate salt-and-pepper noise. By identifying a robust statistical quantity based on the patchwork theory and employing it to embed data, differentiating the bit-embedding process based on the pixel group's distribution characteristics, and using error correction codes and permutation scheme, this technique has achieved both losslessness and robustness. It has been successfully applied to many images, thus demonstrating its generality. The experimental results show that the high visual quality of stego-images, the data embedding capacity, and the robustness of the proposed lossless data hiding scheme against compression are acceptable for many applications, including semi-fragile image authentication. Specifically, it has been successfully applied to authenticate losslessly compressed JPEG2000 images, followed by possible transcoding. It is expected that this new robust lossless data hiding algorithm can be readily applied in the medical field, law enforcement, remote sensing and other areas, where the recovery of original images is desired.

A new MPEG-4 standard for lossless audio coding is going to be published in 2006. This coming international standard consists of two parts: the transform-domain scalable to lossless coding (SLS), and the time-domain audio lossless coding (ALS). In ALS, linear prediction is used to compress the dynamic ranges of the input audio signal. The prediction residual is coded by an entropy coder with either Rice code or arithmetic code. There are two prediction modes in ALS: linear predictive coding (LPC) and cascaded RLS-LMS. As the developer of the RLS-LMS prediction, we present this technology in this paper. In RLS-LMS prediction, the input audio samples go through the cascaded DPCM, RLS, and LMS predictors, whose output predictions are linearly combined to generate a prediction for the current input sample. Through MPLG testings, it has been found that ALS with RLS-LMS prediction provides the best lossless compression ratio compared with SLS, ALS with LPC, and several non-MPEG codecs

This paper presents Advanced Audio Zip (AAZ), a fine grained scalable to lossless (SLS) audio coder that has recently been adopted as the reference model for MPEG-4 audio SLS work. AAZ integrates the functionalities of high-compression perceptual audio coding, fine granular scalable audio coding, and lossless audio coding in a single framework, and simultaneously provides backward compatibility to MPEG-4 Advanced Audio Coding (AAC). AAZ provides the fine granular bit-rate scalability from lossy to lossless coding, and such a scalability is achieved in a perceptually meaningful way, i.e., better perceptual quality at higher bit-rates. Despite its abundant functionalities, AAZ only introduces negligible overhead in terms of lossless compression performance compared with a nonscalable, lossless only audio coder. As a result, AAZ provides a universal yet efficient solution for digital audio applications such as audio archiving, network audio streaming, portable audio playing, and music downloading which were previously catered for by several different audio coding technologies, and eliminates the need for any transcoding system to facilitate sharing of digital audio contents across these application domains.

The recently introduced MPEG standard for lossless audio coding, MPEG-4 Audio Scalable to Lossless (SLS) coding technology, provides a universal audio format that integrates the functionalities of lossy audio coding, lossless audio coding and fine granular scalable audio coding in a single framework. We propose two coding methods that improve the coding efficiency of SLS, namely, a context-based arithmetic code (CBAC) method and a low energy mode code method. These two coding methods work harmonically with the current SLS framework and preserve all its desirable features, such as fine granular scalability, while successfully improving its lossless compression ratio performance.

A new type of region of interest (ROI) is proposed in this paper for scalable video coding with the whole region be the combined SNR and spatial scalability, and a sub-region be a specific choice of spatial resolution and bit rate range. The ROI is applied to design a combined SNR and spatial scalability scheme that is adaptive to customer composition such that an optimal customer oriented scalable tradeoff (COST) can be achieved. The profit can thus be maximized

Most distortion/artifacts in low bit-rate compressed videos are strong and obvious to human eyes, and may even change the spatio-temporal structure of visual objects. Therefore it is important to evaluate the compound perceptual impact of spatial and temporal changes. Recent neurophysiological researches have found that the high-level spatial information (shape and depth, etc.) and temporal information (motion, etc.) are processed separately in two visual pathways in human brains. In this paper, spatial and temporal distortions are evaluated separately in two modules, and are then combined in an integration module. Two subjective viewing experiments are performed. One experiment is to evaluate the subjective quality on temporal distortion only, and second experiment is to evaluate the low bit-rate videos with both spatial and temporal distortions. Experimental results and the associated analysis show that the proposed visual quality metric is in good alignment with human perception

Recently, with the advance of network and storage technologies, it is becoming realistic that people will enjoy high sampling rate, high resolution audio contents with lossless quality. Envisioning of such a need, the international standardization body MPEG has recently introduced a scalable tool for lossless audio coding, namely, MPEG-4 Audio Scalable to Lossless (SLS) coding. MPEG-4 SLS integrates the functionalities of lossless audio coding, perceptual audio coding, and fine granular scalable audio coding in a single framework; meanwhile it provides backward compatibility to MPEG-4 Advanced Audio Coding (AAC) at the bit-stream level. This new tool, in combination with the existing MPEG audio toolset, provides a universal digital audio format that can be used in a variety of application domains such as professional audio, Internet music, consumer electronics, broadcasting

The H.264/AVC video coding standard aims to enable significantly improved compression performance compared to all existing video coding standards. In order to achieve this, a robust rate-distortion optimization (RDO) technique is employed to select the best coding mode and reference frame for each macroblock. As a result, the complexity and computation load increase drastically. This paper presents a fast mode decision algorithm for H.264/AVC intraprediction based on local edge information. Prior to intraprediction, an edge map is created and a local edge direction histogram is then established for each subblock. Based on the distribution of the edge direction histogram, only a small part of intraprediction modes are chosen for RDO calculation. Experimental results show that the fast intraprediction mode decision scheme increases the speed of intracoding significantly with negligible loss of peak signal-to-noise ratio.

The new video coding standard, H.264/MPEG-4 AVC, uses variable block sizes ranging from 4/spl times/4 to 16/spl times/16 in interframe coding. This new feature has achieved significant coding gain compared to coding a macroblock (MB) using fixed block size. However, this feature results in extremely high computational complexity when brute force rate distortion optimization (RDO) algorithm is used. This paper proposes a fast intermode decision algorithm to decide the best mode in intercoding. It makes use of the spatial homogeneity and the temporal stationarity characteristics of video objects. Specifically, spatial homogeneity of a MB is decided based on the MB's edge intensity, and temporal stationarity is decided by the difference of the current MB and it colocated counterpart in the reference frame. Based on the homogeneity and stationarity of the video objects, only a small number of intermodes are selected in the RDO process. The experimental results show that the fast intermode decision algorithm is able to reduce on the average 30% encoding time, with a negligible peak signal-to-noise ratio loss of 0.03 dB or, equivalently, a bit rate increment of 0.6%.

We present a method for extracting local visual perceptual cues and its application for rate control of videophone, in order to ensure the scarce bits to be assigned for maximum perceptual coding quality. The optimum quantization step is determined with the rate-distortion model considering the local perceptual cues in the visual signal. For extraction of the perceptual cues, luminance adaptation and texture masking are used as the stimulus-driven factors, while skin color serves as the cognition-driven factor in the current implementation. Both objective and subjective quality evaluations are given by evaluating the proposed perceptual rate control (PRC) scheme in the H.263 platform, and the evaluations show that the proposed PRC scheme achieves significant quality improvement in block-based coding for bandwidth-hungry applications.

We present an unequal packet loss resilience scheme for robust transmission of video over the Internet. By jointly exploiting the unequal importance existing in different levels of syntax hierarchy in video coding schemes, GOP-level and Resynchronization-packet-level Integrated Protection (GRIP) is designed for joint unequal loss protection (ULP) in these two levels using forward error correction (FEC) across packets. Two algorithms are developed to achieve efficient FEC assignment for the proposed GRIP framework: a model-based FEC assignment algorithm and a heuristic FEC assignment algorithm. The model-based FEC assignment algorithm is to achieve optimal allocation of FEC codes based on a simple but effective performance metric, namely distortion-weighted expected length of error propagation, which is adopted to quantify the temporal propagation effect of packet loss on video quality degradation. The heuristic FEC assignment algorithm aims at providing a much simpler yet effective FEC assignment with little computational complexity. The proposed GRIP together with any of the two developed FEC assignment algorithms demonstrates strong robustness against burst packet losses with adaptation to different channel status.

A new fast algorithm to implement integer modified discrete cosine transform (IntMDCT) is proposed. It is shown that the total rounding operations required for this algorithm are only 2.5N, where N is the block size. As a result, its approximation error is far less than that of directly converted integer transforms. At the same time, the complexity is greatly reduced, which results in improved performance of a lossless audio coding system employing the IntMDCT in terms of compression ratio and complexity costs.

For streaming of pre-encoded bitstreams over constant bit-rate (CBR) channels, the channel bandwidth, the receiver buffer capacity as well as the latency requirement vary greatly from application to application. We propose an algorithm to determine the minimum buffer size and the minimum start-up delay required for streaming a pre-encoded bitstream over CBR channels at any specific bit rate. The proposed method employs geometric operations to derive the optimal determination for low or high bit rates and sub-optimal determination for medium bit rates. The results have been compared with the H.264/AVC hypothetical reference decoder. The proposed approach provides a theoretical insight and a simple but effective algorithm for determining the leaky bucket parameters for video streaming over CBR channels.

The paper presents a fast block INTER mode decision algorithm to improve significantly the time efficiency of the encoder in H.264. It makes use of the spatial homogeneity of a video object's textures and the temporal stationarity characteristics inherent in video sequences. Specifically, the homogeneity decision of a block is based on edge information, and MB differencing is used to judge whether the MB is time-stationary. Based on the above analysis, only parts of inter prediction modes are chosen for RDO (rate distortion optimization) calculation. Experimental results show that the new scheme is able to achieve a reduction of 30% encoding time on average, with a negligible average PSNR loss of only 0.03 dB and a mere 0.6% bit rate increase compared with the original H.264 reference software.

In this paper, we present Advanced Audio Zip (AAZ), a scalable lossless audio coding technology that was recently selected as the reference model for MPEG audio scalable lossless coding (SLS) work. AAZ provides excellent compression performance while delivering fine grain bit-rate scalability from lossy to lossless coding. Moreover, AAZ provides backward compatibility to the MPEG advanced audio coding (AAC) system by embedding an AAC compliant bit-stream into the lossless bit-stream. As a result, AAZ serves as a universal coding solution with functionalities that were previously offered by several distinct audio coding technologies such as lossless audio coding, perceptual audio coding, or scalable audio coding; and maximizes the interchangeability for digital audio contents migrating among these application domains.

This paper presents a rate control scheme for H.264 by introducing the concept of basic unit and a linear prediction model. The basic unit can be a macroblock (MB), a slice, or a frame. It can be used to obtain a trade-off between the overall coding efficiency and the bits fluctuation. The linear model is used to solve the chicken and egg dilemma existing in the rate control of H.264. Both constant bit rate (CBR) and variable bit rate (VBR) cases are studied. Our scheme has been adopted by H.264.

The emerging H.264-AVC video coding standard aims to significantly improve compression performance compared to all existing video coding standards. In order to achieve this, a robust rate-distortion optimization (RDO) technique is employed to select the best coding mode and reference frame for each macroblock. As a result, the complexity and computation load increase drastically. This paper presents a fast mode decision algorithm for H.264 intra prediction based on local edge information. Prior to intra prediction, an edge map is created and a local edge direction histogram is then established for each sub-block. Based on the distribution of the edge direction histogram, only a small part of intra prediction modes are chosen for RDO calculation. Experimental results show that the last intra mode decision scheme increases the speed of intra coding significantly with negligible loss of PSNR.

We propose a simple iterative method to verify whether a coded bitstream conforms to a hypothetical reference decoder (HRD). A concept of maximum tolerated delay (MTD) is introduced to study the possible low-delay operation, such that we can bound the degree of incorrect motion rendition caused by the variation in end to end delay in the neighborhood of big pictures. Our method can be used in the design of a rate control algorithm to improve the possibility of a coded bitstream that conforms to the HRD.

Recently, among various data hiding techniques, a new subset, lossless data hiding, has drawn tremendous interest. Most existing lossless data hiding algorithms are, however, fragile in the sense that they can be defeated when compression or other small alteration is applied to the marked image. The method of C. De Vleeschouwer et al. (see IEEE Trans. Multimedia, vol.5, p.97-105, 2003) is the only existing semi-fragile lossless data hiding technique (also referred to as robust lossless data hiding), which is robust against high quality JPEG compression. We first point out that this technique has a fatal problem: salt-and-pepper noise caused by using modulo 256 addition. We then propose a novel robust lossless data hiding technique, which does not generate salt-and-pepper noise. This technique has been successfully applied to many commonly used images (including medical images, more than 1000 images in the CorelDRAW database, and JPEG2000 test images), thus demonstrating its generality. The experimental results show that the visual quality, payload and robustness are acceptable. In addition to medical and law enforcement fields, it has been applied to authenticate losslessly compressed JPEG2000 images.

Conventional rate control schemes focus on the problem of finding an optimal quantization value for P- and B-frames. No rate control is available for the encoding of I-frames. This could pose big problems due to the large number of bits an I-frame could generate, and due to the fact that the number of bits varies drastically from sequence to sequence, depending on their image complexity. This problem becomes severe especially at very low bit rate. Therefore, a mechanism to allocate data bits to an I-frame according to its complexity is indispensable in order to have constant coding quality. This work presents a mechanism to establish for I-frames a generic relationship between the quantization value, data bits, and their image complexity. Experimental results show that this generic relationship provides a fairly accurate estimation of quantization value for an I-frame at given data bits and image complexity, and is very useful in controlling the data bits generated by an I-frame.

The H.264 video coding standard can achieve considerably higher coding efficiency than previous standards. In order to achieve this, a robust rate-distortion optimization (RDO) technique is employed to select the best coding mode for each macroblock. As a result. the encoder complexity is increased considerably. This paper presents a directional field based fast intra mode decision algorithm to improve the encoder's efficiency. Prior to intra prediction, the directional field is calculated for all the block size to decide the dominant edge direction in the blocks. Based on the edge direction information, only a small number of prediction modes are chosen for RDO calculation. Experimental results show that the fast intra mode decision algorithm increases the speed of intra coding significantly with negligible loss of PSNR

Many rate control algorithms focus on the adjustment of quantisation values to retain a certain buffer level, and arbitrary frame-skipping is often needed to keep the buffer from overflow at very low bit-rates. A content adaptive rate control is proposed to optimise the balance between spatial and temporal quality via active frame-skipping. The occurrence of frame-skipping is jointly dependent on the temporal and spatial quality of the video, and on the fullness of the buffer. This helps to achieve a consistent spatial and temporal quality and to enhance the overall perceptual quality. Experimental results show that the new scheme is simple but very effective, with large average PSNR gains and consistently improved visual quality, and the improvement in perceptual quality is much more significant than that in average PSNRs.

Block-based transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization. and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. Instead of using the traditional pixel discontinuity along the block boundary, we use the edge directional information of the images. The new algorithm does not need the exact location of the block boundary thus is invariant to the displacement, rotation and scaling of the images. Experiments on various still images and videos show that the new blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce blocking artifact measurement consistent with subjective rating

The modified discrete cosine transform (MDCT) has been widely used in many transform audio coding algorithms such as MPEG-1/2 layer III (mp3), MPEG-2/4 AAC, Dolby AC2/AC3, and numerous experimental audio coding algorithms. In this paper, we study the probabilistic distribution properties of the MDCT coefficient for audio signals. It is shown that the generalized Gaussian function with distribution parameter r=0.5 or r=1 (Laplacian) provides a good approximation to the distributions of MDCT coefficients for a variety of audio signals. Results from our study also show that although the distribution of these coefficients is not strictly Laplacian, the divergence between them is in fact very small. Therefore, it leads to only marginal redundancy if these coefficients are simply coded with some low-complexity codes designed for Laplacian sources.

This work proposes a unified authentication framework for JPEG2000 images, which consists of fragile, lossy and lossless authentication for different applications. The authentication strength can be specified using only one parameter called lowest authentication bit-rate (LABR), bringing much convenience to users. The lossy and lossless authentication could survive various incidental distortions while being able to allocate malicious attacks. In addition, with lossless authentication, the original image can be recovered after verification if no incidental distortion is introduced.

Fast block motion estimation normally consists of low-resolution coarse search and the following fine-resolution inner search. Most motion estimation algorithms developed attempt to speed up the coarse search without considering accelerating the focused inner search. On top of the hexagonal search method recently developed, an enhanced hexagonal search algorithm is proposed to further improve the performance in terms of reducing number of search points and distortion, where a novel fast inner search is employed by exploiting the distortion information of the evaluated points. Our experimental results substantially justify the merits of the proposed algorithm.

This paper presents a bit-plane coding algorithm for Laplacian distributed sources that are commonly encountered in signal compression applications. By exploiting the statistical characteristics of the sources, the proposed algorithm achieves a rate-distortion performance that is essentially comparable to an optimal nonscalable scalar quantizer, while at the same time operates at a complexity level suitable for most practical implementations.

In this paper, we propose a new video post-processing algorithm for reducing coding artifacts. The algorithm is based on regularized image restoration technique, in which a nonconvex regularization function is used to enforce smoothness constraints on the spatial image pixels for suppressing coding artifacts while preserving important image attribute. Temporal regularization is carried out along the motion trajectories. We apply half-quadratic regularization and piecewise constraint strategy to simplify the optimization problem. Explicit filtering formulae are obtained and a recursive filtering algorithm is developed. Experimental results demonstrate that the proposed method can significantly improve both subjective and objective quality of MPEG-4 coded video sequences in comparison with the postprocessing technique in MPEG-4.

This paper proposes an adaptive frame layer rate control scheme for H.264 by introducing a linear model to predict the mean absolute difference (MAD) of current frame by that of previous one. The target bit rate for each frame is computed by adopting a fluid flow traffic model and linear tracking theory. The corresponding quantization parameter is computed by using a quadratic rate-distortion model. The rate distortion optimization (RDO) is then performed for all macroblocks (MBs) in the current frame by the quantization parameter. Both constant bit rate (CBR) and variable bit rate (VBR) cases are studied. The average PSNR is improved up to 0.75 dB compared to an encoder with fixed quantization parameter.

We introduce a PDA-based live video streaming system on GPRS network based on MPEG-4 video compression standard. Due to the limited computational resources of PDA, all the key modules of MPEG-4 codec are efficiently implemented and optimized such as multithreading, buffer design, wireless communication, encoder and decoder. Several novel techniques are developed in the coding, streaming as well as the post- processing stages of the system.

This paper presents advanced audio zip (AAZ), an audio codec that provides the fine granular bit-rate scalability from lossy to lossless coding. Perceptually embedded coding principle is employed in AAZ to provide lossy reconstruction with optimal perceptual quality at intermediate bit-rates. AAZ also provides the backward compatibility where the lossless bit-stream embeds a compliant MPEG-4 AAC bit-stream.

We formulate a congestion control problem for multipoint videoconferencing by introducing the concept of generalized fairness. A numerical method is provided to solve such a congestion control problem. The proposed method is much simpler than an earlier proposed method. This is desirable because congestion control is executed in real time.

In block motion estimation, a search pattern with a different shape or size has a very important impact on search speed and distortion performance. A square-shaped search pattern is adopted in many popular fast algorithms. Recently, a diamond-shaped search pattern was introduced in fast block motion estimation and has exhibited a faster search speed. Based on an in-depth examination of the influence of the search pattern on speed performance, we propose a novel algorithm using a hexagon-based search pattern to achieve further improvement. The hexagon-based search pattern is investigated in comparison with diamond search pattern and demonstrates significant speedup gain over the diamond-based search. Analysis shows that a speed improvement rate of the hexagon-based search (HEXBS) algorithm over the diamond search (DS) algorithm can be over 80% for locating some motion vectors in certain scenarios. In short, the proposed HEXBS algorithm can find the same motion vector with fewer search points than the DS algorithm. Generally speaking, the larger the motion vector, the more search points the. HEXBS algorithm can save, which is further justified by experimental results.

In block motion estimation, search patterns with different shape or size have a very important impact on search speed and distortion performance. In this paper, we propose a novel algorithm using a hexagon-based search (HEXBS) pattern for fast block motion estimation. The proposed HEXBS algorithm may find any motion vector with fewer search points than the diamond search (DS) algorithm. The speedup gain of the HEXBS method over the DS algorithm is more striking for finding large motion vectors. Experimental results substantially justify the fastest performance of the HEXBS algorithm compared with several other popular fast algorithms.

For compression of audio waveform, prediction is one of the important key components. We propose a novel multi-stage adaptive linear predictor (MSALP) for the prediction of high fidelity audio waveform. The MSALP achieves higher prediction gain compared with conventional linear predictor (LP). Besides, the MSALP uses less number of coefficients. The MSALP is embedded into a lossless audio waveform compression system. As a result, the system compression ratio is obviously improved. By selecting known lossless audio waveform compression algorithms, some comparison results are presented.

This paper presents our study on the feasibility and effectiveness of using the MELP (mixed excitation linear prediction) model for coding wideband (7 kHz) speech signals at a transmission bit rate of 8 kbps. In order to achieve a reasonably good subjective quality for the decoded speech while maintaining a low operating bit rate at the same time, modifications to the pitch estimation, LP analysis/synthesis and post filtering stages of the original MELP model are discussed. Informal listening tests show that the subjective quality of the decoded speech of the proposed coder is rated to be slightly better than the MPEG-4 CELP coder operating at 14.4 kbps for both male and female utterances. The subjective quality of the decoded female utterances from the proposed coder operating at 8.4 kbps is rated to be comparable to that produced by the ITU G.722 coder operating at 48 kbps.

This paper describes a low bit rate standalone portable video communication system developed for wireless applications. The video codec is based on H.263, and the audio codec is based on G.723.1. The transmission bandwidth is limited to 25 kHz. In order to have reasonable good video and audio quality, the source bit rate is set to 38 kbps. This includes video, audio and synchronization. The bit stream is embedded with 26 kbps for the error protection, resulted in a total of 64 kbps. A 16-QAM is used for the modulation in order to meet the bandwidth requirement. The whole system deployed three general purpose DSP for the real time implementation of video coding, audio coding, channel coding and system control. Besides, an RF module is developed for the transmission on UHF band.

In this paper, we investigate methods for the extraction of non-textual information from spoken sentences in order to identify the emotional state of the speaker. We propose a method based on judging the flatness of the pitch contour. The results of our experiments show that the proposed method achieves reasonably good recognition rates: more than 90% for male speakers and around 80% for female speakers.

We present a low bit rate base band speech communication system by using the PC and Windows environment. The speech codec is the US DoD standard MELP with a bit rate of 2.4 kbps. This system is especially suitable for a channel transmission rate of less than 2.4 kbps environment. The system provides an RS-232 serial port interface for a normal modem as well as a TCP/IP interface for LAN. A Pentium 133 with a normal sound card is enough for such full duplex implementation.