Hardware-Software Implementation of MPEG-4 Video Codec

This dissertation reports on rate-distortion optimized and computation-constrained video coding algorithms which yield effective and efficient block-based video encoders. We first propose a new cost function for motion estimation which can achieve good tradeoffs among motion vector bit rate, compensation distortion, and number of computations. Based on the new cost function, we propose a predictive motion estimation algorithm which can effectively determine the size of the search region according to the statistics of the motion field. The proposed motion estimation algorithm allows control of the motion vector bit rate and the computational cost, simultaneously. We also develop two efficient rate-distortion optimized coding mode selection algorithms, based on thresholding and finite state machine (FSM) methods, respectively. The thresholding method can eliminate consideration of the computationally expensive modes. The FSM method determines the test orders of the modes and associated parameters by exploiting the local statistics of the input video sequence. The proposed two methods can reduce substantially the computation requirements as compared to the full search mode selection method. Based on the proposed motion estimation and mode selection algorithms, we implement an H.263-based video coder and an MPEG-2, compliant video coder for very low bit rate video applications, and high bit rate interlaced video applications, respectively. The resulting video coders achieve excellent tradeoffs among bit rate, quality, and computational complexity. In fact, experimental results show that our video coders outperform the best known video coders in terms of compression performance and encoding speed.

Motion Estimation (ME) is the most computationally intensive part of video compression systems. Multiple reference frame (MRF) ME used in H.264 standard increases the video coding efficiency at the expense of increased computational complexity and power consumption. Therefore, in this paper, we present a reconfigurable baseline H.264 video encoder hardware in which the number of reference frames used for MRF ME can be configured based on the application requirements in order to trade-off video coding efficiency and power consumption. The proposed H.264 video encoder hardware is based on an existing low cost H.264 intra frame coder hardware and it includes new reconfigurable MRF ME, mode decision and motion compensation hardware. The proposed H.264 video encoder hardware is capable of processing 55 CIF (352×288) frames per second and its power consumption ranges between 115mW and 235mW depending on the number of reference frames used for MRF ME.

Fixed length entropy codes (FLC) have been employed as an alternative to the usual variable length codes (VLC) in video codecs. The effect of a transmission error in an FLC coded stream does not propagate beyond the corrupted codeword because of its fixed parsing structure. This paper presents a new decoding algorithm for FLC compressed video streams that fully exploits the error resilience properties of FLC codes combined with spatial synchronization points. While maintaining the compression efficiency of VLC coded video streams, the proposed solution is a novel idea to combat the consequences of transmission errors and it is totally compatible with more traditional solutions such as error concealment and forward error correcting codes.

Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of two conjugate PAR images. To evaluate the proposed algorithm, digital XCAT and physical dynamic cardiac phantom datasets are used. The XCAT phantom datasets were generated with heart rates of 70 and 100 bpm, respectively, by assuming a system rotation time of 300 ms. A physical dynamic cardiac phantom was scanned using a slowly rotating XCT system so that the effective heart rate will be 70 bpm for a system rotation speed of 300 ms. In the XCAT phantom experiment, motion-compensated 3D images obtained from the proposed algorithm show coronary arteries with fewer motion artifacts for all phases. Moreover, object boundaries contaminated by motion are well restored. Even though object positions and boundary shapes are still somewhat different from the ground truth in some cases, the authors see that visibilities of coronary arteries are improved noticeably and motion artifacts are reduced considerably. The physical phantom study also shows that the visual quality of motion-compensated images is greatly improved. The authors propose a novel PAR image-based cardiac motion estimation and compensation algorithm. The algorithm requires an angular scan range of less than 360°. The excellent performance of the proposed algorithm is illustrated by using digital XCAT and physical dynamic cardiac phantom datasets.

The problem of error control and concealment in video communication is becoming increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks and the Internet. This paper reviews the techniques that have been developed for error control and concealment. These techniques are described in three categories according to the roles that the encoder and decoder play in the underlying approaches. Forward error concealment includes methods that add redundancy at the source end to enhance error resilience of the coded bit streams. Error concealment by postprocessing refers to operations at the decoder to recover the damaged areas based on characteristics of image and video signals. Last, interactive error concealment covers techniques that are dependent on a dialogue between the source and destination. Both current research activities and practice in international standards are covered.

Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies, a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed. Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region. Then the motion region was extracted to carry out motion estimation and motion compensation on it. The experiment results show that the encoding efficiency of motion vector is promoted, the complexity of motion estimation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Resolution Motion Estimation (MRME) is improved.

This paper introduces a novel scheme of motion estimation (ME) and motion compensation (MC) in wavelet transform (WT) video coding. The scheme is unique in that half-pixel resolution ME and MC are applied on filtered coefficients ahead of decimation to preserve motion consistency and yet achieve minimal prediction residue. An efficient motion-compensated WT video coding system is built based on the proposed ME and MC. In the coding scheme, according to the property of embedded zerotree wavelet (EZW) coding, the mean square error (MSE) criterion is used in ME instead of normally adopted sum of absolute difference, and an overlapped MC algorithm is developed to combat the block effect introduced by block-based ME and improve peak signal-to-noise ratio (PSNR) performance. The superior performance of the proposed scheme is demonstrated with experimental results.

: The research tasks are: Task 1, Scalable Coding; Task 2, Alternatives to variable length coding (VLC); and Task3, Packetizing for Error Concealment. Initial work on Task 1 built on research from a prior DARPA contract, and resulted in a scalable video coder with the unique property of scalable transmission at six resolution/frame-rate combinations. Task 2 work combined fixed and variable length coding (VLC) into a joint coding approach with distinct robustness advantages, while giving up only a slight amount of performance versus straight VLC coding in the noise-free case. Task 3 Packetzing for Error Concealment explored the new technique dispersive packetization and combined it with error concealment in a state-of-the-art subband/wavelet image coder. An ns-2 network simulation revealed substantial robustness to packet loss error, with useable images recovered under packet loss rates at high as 30%, thus implementing the graceful degradation property.

Motion estimation and motion compensation (MEMC) has been applied inside the wavelet-transformed domain for video compression at low bit rates. However, pixel-based motion estimation in the wavelet domain is not as straightforward as in the spatial domain due to the shift variance property caused by decimation. The paper finds a new wavelet-based motion estimation and compensation method, named as the sub-decimation decomposition method, to perform shift invariant motion estimation inside the wavelet transformed domain, so that better matching blocks are compensated to achieve more efficient video compression.

Distributed Video Coding (DVC) is a new paradigm for video compression based on the information theoretical results of Slepian and Wolf (SW), and Wyner and Ziv (WZ). While conventional coding has a rigid complexity allocation as most of the complex tasks are performed at the encoder side, DVC enables a flexible complexity allocation between the encoder and the decoder. The most novel and interesting case is low complexity encoding and complex decoding, which is the opposite of conventional coding. While the latter is suitable for applications where the cost of the decoder is more critical than the encoder's one, DVC opens the door for a new range of applications where low complexity encoding is required and the decoder's complexity is not critical. This is interesting with the deployment of small and battery-powered multimedia mobile devices all around in our daily life. Further, since DVC operates as a reversed-complexity scheme when compared to conventional coding, DVC also enables the interesting scenario of low complexity encoding and decoding between two ends by transcoding between DVC and conventional coding. More specifically, low complexity encoding is possible by DVC at one end. Then, the resulting stream is decoded and conventionally re-encoded to enable low complexity decoding at the other end. Multiview video is attractive for a wide range of applications such as free viewpoint television, which is a system that allows viewing the scene from a viewpoint chosen by the viewer. Moreover, multiview can be beneficial for monitoring purposes in video surveillance. The increased use of multiview video systems is mainly due to the improvements in video technology and the reduced cost of cameras. While a multiview conventional codec will try to exploit the correlation among the different cameras at the encoder side, DVC allows for separate encoding of correlated video sources. Therefore, DVC requires no communication between the cameras in a multiview scenario. This is an advantage since communication is time consuming (i.e. more delay) and requires complex networking. Another appealing feature of DVC is the fact that it is based on a statistical framework. Moreover, DVC behaves as a natural joint source-channel coding solution. This results in an improved error resilience performance when compared to conventional coding. Further, DVC-based scalable codecs do not require a deterministic knowledge of the lower layers. In other words, the enhancement layers are completely independent from the base layer codec. This is called the codec-independent scalability feature, which offers a high flexibility in the way the various layers are distributed in a network. This thesis addresses the following topics: First, the theoretical foundations of DVC as well as the practical DVC scheme used in this research are presented. The potential applications for DVC are also outlined. DVC-based schemes use conventional coding to compress parts of the data, while the rest is compressed in a distributed fashion. Thus, different conventional codecs are studied in this research as they are compared in terms of compression efficiency for a rich set of sequences. This includes fine tuning the compression parameters such that the best performance is achieved for each codec. Further, DVC tools for improved Side Information (SI) and Error Concealment (EC) are introduced for monoview DVC using a partially decoded frame. The improved SI results in a significant gain in reconstruction quality for video with high activity and motion. This is done by re-estimating the erroneous motion vectors using the partially decoded frame to improve the SI quality. The latter is then used to enhance the reconstruction of the finally decoded frame. Further, the introduced spatio-temporal EC improves the quality of decoded video in the case of erroneously received packets, outperforming both spatial and temporal EC. Moreover, it also outperforms error-concealed conventional coding in different modes. Then, multiview DVC is studied in terms of SI generation, which differentiates it from the monoview case. More specifically, different multiview prediction techniques for SI generation are described and compared in terms of prediction quality, complexity and compression efficiency. Further, a technique for iterative multiview SI is introduced, where the final SI is used in an enhanced reconstruction process. The iterative SI outperforms the other SI generation techniques, especially for high motion video content. Finally, fusion techniques of temporal and inter-view side informations are introduced as well, which improves the performance of multiview DVC over monoview coding. DVC is also used to enable scalability for image and video coding. Since DVC is based on a statistical framework, the base and enhancement layers are completely independent, which is an interesting property called codec-independent scalability. Moreover, the introduced DVC scalable schemes show a good robustness to errors as the quality of decoded video steadily decreases with error rate increase. On the other hand, conventional coding exhibits a cliff effect as the performance drops dramatically after a certain error rate value. Further, the issue of privacy protection is addressed for DVC by transform domain scrambling, which is used to alter regions of interest in video such that the scene is still understood and privacy is preserved as well. The proposed scrambling techniques are shown to provide a good level of security without impairing the performance of the DVC scheme when compared to the one without scrambling. This is particularly attractive for video surveillance scenarios, which is one of the most promising applications for DVC. Finally, a practical DVC demonstrator built during this research is described, where the main requirements as well as the observed limitations are presented. Furthermore, it is defined in a setup being as close as possible to a complete real application scenario. This shows that it is actually possible to implement a complete end-to-end practical DVC system relying only on realistic assumptions. Even though DVC is inferior in terms of compression efficiency to the state of the art conventional coding for the moment, strengths of DVC reside in its good error resilience properties and the codec-independent scalability feature. Therefore, DVC offers promising possibilities for video compression with transmission over error-prone environments requirement as it significantly outperforms conventional coding in this case.

A technique is presented that incorporates an irregular triangle mesh into wavelet-domain motion-estimation and motion-compensation using a shift-invariant redundant wavelet transform. Triangle vertices are identified by a simple correlation operator locating image edges in the wavelet subbands, while motion compensation takes place through an affine transformation mapping triangles from one frame to the next. The motion-compensated residual is downsampled to a non-redundant form which is then coded using any wavelet-based still-image coder. Experimental results indicate that the combined approach outperforms either technique applied separately,, in addition, the proposed method outperforms a variety of motion-estimation and motion-compensation approaches operating in both the spatial and wavelet domains.

This paper presents an accurate bit rate and quality control algorithm for 3D multiview sequences. We remodel the quadratic rate-distortion model for 3D multiview sequences based on their picture types. The proposed method consists of two levels for more accurate bits rate control. In a frame level, it sets quantization parameters based on HVS (Human Visual System) and reduces error bits by remodeling rate-quantization. In a MB level, rate control is activated to provide stricter buffer regulations and higher bit rate encoding based on the target bits and the quantization parameters calculated at the frame level. The proposed algorithm shows improvements in rate control as well as in PSNR compared to the conventional methods. It also provides more accurate rate control and higher image quality than TM5 and TMN8 at various bits rates.

The rate-constrained (R-D) motion estimation techniques have been presented to improve the conventional block-matching algorithm by using a joint rate and distortion criterion. This paper presents two motion estimation algorithms using Kalman filter to further enhance the performance of the conventional R-D motion estimation at a relative low computational cost. The Kalman filter exploits the correlation of block motion to achieve higher precision of motion estimation and compensation. In the first algorithm, the Kalman filter is utilized as a postprocessing to raise the motion compensation accuracy of the conventional R-D motion estimation. In the second algorithm, the Kalman filter is embedded into the optimization process of R-D motion estimation by defining a new R-D criterion. It further improves the rate-distortion performance significantly.

An efficient MPEG-2 to MPEG-4 video transcoder is presented in this paper. We consider the transcoding from high quality and bit rate MPEG-2 video with larger image size (e.g. 4CIF/4SIF, CIF) to lower quality and bit rate MPEG-4 video with smaller image size (e.g. CIF, QCIF). First, the transcoder needs to down-sample the input MPEG-2 video. Since the motion vectors carried by the MPEG-2 stream will be reused in the transcoding process, they are sub-sampled besides the frame pixels, and the coding mode for each down-sampled macroblock is examined. A new rate control method is proposed to convert the high bit rate MPEG-2 video to the low bit rate MPEG-4 counterpart. The proposed rate control scheme adjusts the frame rate and the frame quantization step size simultaneously according to the channel bandwidth to achieve a good temporal-spatial quality tradeoff. Due to the reuse of motion vectors, key frames (i.e. I and P frames) cannot be skipped to maintain the prediction sequential order, while some B frames containing less temporal information may be skipped in transcoding to save the bit rate. Skipped B frames can be reconstructed at the decoder to ensure the full frame rate playback. The TM7 quadratic Rate-Qtz model is adopted in the proposed rate control scheme to calculate the re-quantization step size from the given target bit. Simulations show that the proposed MPEG-2 to MPEG-4 video transcoder with rate control can out-perform the basic MPEG transcoder that adjusts the re-quantization step size at a constant frame rate. The complexity of the proposed transcoder is low so that it can be used in real-time applications.

This chapter shows how neural fuzzy systems can improve motion estimation and compensation for video compression. Motion estimation and compensation are key parts of video compression. They help remove temporal redundancies in images. Most motion estimation algorithms neglect the strong-temporal correlations within the motion field. The search windows stay the same through the image sequences and the estimation needs heavy computation. We use an unsupervised neural vector quantizer system can use the temporal correlation of the motion field to estimate the motion vectors. First-order and second-order statistics of the motion vectors give ellipsoidal search windows. This algorithm reduces the search area and entropy and gives clustered motion fields. Motion-compensated video coding further assumes that each block of pixels moves with uniform translational motion. This often does not hold and can produce block artifacts. We use a supervised neural fuzzy system to compensate for the overlapped block motion. This fuzzy system uses the motion vectors of neighboring blocks to map the prior frame’s pixel values to the current pixel value. The neural fuzzy system used 196 rules that came from the prior decoded frame. The fuzzy system learns and updates its rules as it decodes the image. The fuzzy system also improved the compensation accuracy. The appendix derives both the fuzzy system and the supervised neural-like learning laws that tune its parameters.