Wyner–Ziv-based bidirectionally decodable video coding

In this paper, we propose a novel Wyner–Ziv-based video compression scheme which supports encoding a new type of inter frame called ‘M-frame’. Different from traditional multi-hypothesis inter frames, the M-frame is specially compressed with its two neighbor frames as reference at the encoder, but can be identically reconstructed by using any one of them as prediction at the decoder. Based on this, the proposed Wyner–Ziv-based bidirectionally decodable video compression scheme supports decoding the frames in a video stream in both temporal order and reverse order. Unlike the other schemes which support reverse playback, our scheme achieves the reversibility with low extra cost of storage and bandwidth. In error-resilient test, our scheme outperforms H.264 based schemes up to 3.5 dB at same bit rate. The proposed scheme also provides more flexibility for stream switching.     

A fine-grain distortion and complexity aware parameter tuning model for the H.264/AVC encoder

Most existing video encoders currently used in mobile applications are unable to gracefully degrade their output quality as the battery life nears its end. In other words, they cannot manage power consumption to efficiently utilize the available power resources. To be able to effectively adapt to changes in the encoder′s software and hardware platforms, especially due to the power limitations of mobile devices, the effect of encoder parameters on the encoding quality and power consumption has to be represented using a Rate–Distortion–Complexity (R–D–C) model. Most existing R–D–C models only consider macroblock level parameters, and overlook other higher level parameters that may have a more significant impact on complexity. In this paper, the distortion and complexity of the H.264/AVC encoder is controlled considering a subset of higher level encoding parameters consisting of search range, number of reference frames, and motion vector resolution. First, the complexity of full and fast motion estimation methods is modeled in an implementation and platform independent manner. Then, using this complexity model, a common encoding parameter setting table is derived, which leads to the least amount of distortion for each complexity condition. Finally, a complexity control mechanism is proposed which tunes the encoding parameters in a real-time manner. The proposed model can be combined with other existing macroblock level models in order to design a two-phase fine grain complexity controller. Simulation results indicate that when our method is integrated with the direct resource allocation (DRA) approach, performance increases by an average of 1.02 dB and 1.06 dB for full and fast motion estimation approaches, respectively.     

Optimal-correlation-based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient joint reconstruction by leveraging more realistic signal models is still an open challenge. In this paper, we present a novel optimal-correlation-based reconstruction method for compressively sampled videos from multiple measurement vectors. In our method, the sparsity is mainly exploited through inter-signal correlations rather than the traditional frequency transform, wherein the optimization is not only over the signal space to satisfy data consistency but also over all possible linear correlation models to achieve minimum-l₁-norm correlation noise. Additionally, a two-phase Bregman iterative based algorithm is outlined for solving the optimization problem. Simulation results show that our proposal can achieve an improved reconstruction performance in comparison to the conventional approaches, and especially, offer a 0.7–9.9 dB gain in the average PSNR for DCVS.     

Novel rate control scheme for intra frame video coding with exponential rate–distortion model on H.264/AVC

Rate control regulates the output bit rate of a video encoder in order to obtain optimum visual quality within the available network bandwidth and to maintain buffer fullness within a specified tolerance range. Due to the benefits of intra-only encoding, such as less computational cost and less latency, it has been more and more widely used. In this paper, we propose an accurate intra-only rate control scheme for H.264/AVC, which includes a novel complexity measurement and a new rate–distortion (R–D) model. We also propose a linear rate–complexity model which takes the intercept into consideration to reduce the estimation error. The proposed R–D model is integrated by the linear rate–complexity model and an exponential rate–quantization model. Based on theoretical analysis and experimental validation, the proposed scheme has high bits prediction precision, and it can also accurately handle buffer fullness. Compared with JVT-W042, our algorithm achieves higher average PSNR and improves the coding quality up to 0.35 dB.     

Fast coding unit partitioning method based on edge detection for HEVC intra-coding

High efficiency video coding (HEVC) standard is the latest video coding standard generation. It employs powerful coding tools to obtain improved compression efficiency. To better exploit the redundancies, HEVC adopts a very flexible quad-tree coding structure, allowing the encoder to use a block partition that matches the image features. This exhaustive technique may achieve a higher coding efficiency; however, it induces a significant computational complexity in the encoding engine. This paper proposes a new texture parameter for classifying digital videos as a first contribution and then introduces an efficient coding unit (CU) partitioning algorithm based on the early defined texture parameter in order to speed up the encoding process. In fact, the proposed technique is based on edge detection by performing SOBEL filtering in order to decide the appropriate CU size. Compared to the original HEVC, the average execution time-saving is about 31 % while maintaining almost the same output video quality.     

Frame-wise detection of relocated I-frames in double compressed H.264 videos based on convolutional neural network

Relocated I-frames are a key type of abnormal inter-coded frame in double compressed videos with shifted GOP structures. In this work, a frame-wise detection method of relocated I-frame is proposed based on convolutional neural network (CNN). The proposed detection framework contains a novel network architecture, which initializes with a preprocessing layer and is followed by a well-designed CNN. In the preprocessing layer, the high-frequency component extraction operation is applied to eliminate the influence of diverse video contents. To mitigate overfitting, several advanced structures, such as 1 × 1 convolutional filter and the global average-pooling layer, are carefully introduced in the design of the CNN architecture. Public available YUV sequences are collected to construct a dataset of double compressed videos with different coding parameters. According to the experiments, the proposed framework can achieve a more promising performance of relocated I-frame detection than a well-known CNN structure (AlexNet) and the method based on average prediction residual.     

Visual quality assessment for web videos

The advent of video-sharing sites such as YouTube has led to an unprecedented Internet delivery of community-contributed video content. However, most of these videos are not quality-controlled. This paper reports a first attempt towards assessing web videos in terms of visual quality with significant tests on 30k web videos. We regard the quality assessment as a two-class classification problem: features motivated from domain knowledge are extracted to be the visual representation while the overall quality is the two-class label. Observing that web videos are characterized by a much higher diversity of content, genres, capture devices, and skills than any other traditional video program, we propose to combine two types of domain knowledge to predict the perceived quality score. One of the domain knowledge types is the spatiotemporal factors affecting the overall perceived quality of web videos, including four spatial factors and two temporal factors. We study the effectiveness of various spatiotemporal factors and propose some novel spatial factors pertaining the characteristics of web videos. The other is the video editing style, including shot editing style, frame size, and black side ratio. Comprehensive experiments and evaluations over 30k web videos which add up to 1200 h in total demonstrated the effectiveness of the proposed approach. We show some preliminary results for application to filtering and re-ranking of retrieved web videos.     

Distortion free image-in-image communication with implementation in FPGA

The proliferation of the digitized media (audio, image and video) introduces a challenging problem for data transmission in the network environment. In this paper, a novel, simple and low cost algorithm that serves the purpose of distortion free covert image-in-image communication is proposed. Its very large scale integration (VLSI) implementation using field programmable gate array (FPGA) is also developed. A binary equivalent message signal is developed first from the combination of the auxiliary gray scale image information and the carrier gray scale image (original) using channel coding and spatial bi-phase modulation scheme. The auxiliary image information is then decoded from the distorted/distortion free version of the original image using binary message under certain noise constraint. Implementation of the proposed low cost algorithm can be speeded up significantly by hardware realization. The developed hardware design allows data transmission at the rate of 4.706 Mbits/s at 80 MHz clock frequency.     

Performance evaluation of (D)APSK modulated coherent optical OFDM system

Performance of amplitude and phase shift keying (APSK) modulated coherent optical orthogonal frequency division multiplexing (CO-OFDM) with and without differential encoding is investigated. Numerical simulations based on 40 Gbit/s single-channel and 5 ^* 40 Gbit/s wavelength division multiplexing transmission are performed, and the impacts of amplified spontaneous emission noise, laser linewidth, chromatic dispersion, and fiber nonlinearity on the system performance are analyzed. The results show that compared with conventional 16 quadrature amplitude modulation (QAM) modulated optical OFDM signal, although 16(D)APSK modulated optical OFDM signal has a lower tolerance towards amplified spontaneous emission (ASE) noise, it has a higher tolerance towards fiber nonlinearity such as self-phase modulation (SPM) and cross-phase modulation (XPM): the optimal launch power and the corresponding Q² factor of 16(D)APSK modulated OFDM signal are respectively 2 dB and 0.5 dB higher than 16QAM modulated optical OFDM signal after 640 km transmission, both in single-channel and WDM CO-OFDM systems. Although the accumulated CD decreases the peak-to-average power ratio (PAPR) during transmission, 16(D)APSK modulated OFDM signal will still remain an advantage compared with 16QAM modulated OFDM signal up to 1000 km single-channel transmission, meanwhile relaxing the needs for training symbols and pilot subcarriers and consequently increase the spectral efficiency.     

Advanced side information creation techniques and framework for Wyner–Ziv video coding

Recently, several distributed video coding (DVC) solutions based on the distributed source coding (DSC) paradigm have appeared in the literature. Wyner–Ziv (WZ) video coding, a particular case of DVC where side information is made available at the decoder, enable to achieve a flexible distribution of the computational complexity between the encoder and decoder, promising to fulfill novel requirements from applications such as video surveillance, sensor networks and mobile camera phones. The quality of the side information at the decoder has a critical role in determining the WZ video coding rate-distortion (RD) performance, notably to raise it to a level as close as possible to the RD performance of standard predictive video coding schemes. Towards this target, efficient motion search algorithms for powerful frame interpolation are much needed at the decoder. In this paper, the RD performance of a Wyner–Ziv video codec is improved by using novel, advanced motion compensated frame interpolation techniques to generate the side information. The development of these type of side information estimators is a difficult problem in WZ video coding, especially because the decoder only has available some reference, decoded frames. Based on the regularization of the motion field, novel side information creation techniques are proposed in this paper along with a new frame interpolation framework able to generate higher quality side information at the decoder. To illustrate the RD performance improvements, this novel side information creation framework has been integrated in a transform domain turbo coding based Wyner–Ziv video codec. Experimental results show that the novel side information creation solution leads to better RD performance than available state-of-the-art side information estimators, with improvements up to 2 dB; moreover, it allows outperforming H.264/AVC Intra by up to 3 dB with a lower encoding complexity.     

No-reference pixel based video quality assessment for HEVC decoded video

This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by the High Efficiency Video Coding (HEVC) scheme. The assessment is performed without access to the bitstream. The proposed analysis is based on the transform coefficients estimated from the decoded video pixels, which is used to estimate the level of quantization. The information from this analysis is exploited to assess the video quality. HEVC transform coefficients are modeled with a joint-Cauchy probability density function in the proposed method. To generate VQA features the quantization step used in the Intra coding is estimated. We map the obtained HEVC features using an Elastic Net to predict subjective video quality scores, Mean Opinion Scores (MOS). The performance is verified on a dataset consisting of HEVC coded 4 K UHD (resolution equal to 3840 × 2160) video sequences at different bitrates and spanning a wide range of content. The results show that the quality scores computed by the proposed method are highly correlated with the mean subjective assessments.     

Dictionary learning based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient reconstruction by leveraging more realistic signal models that go beyond simple sparsity is still an open challenge. In this paper, we propose a novel “undersampled” correlation noise model to describe compressively sampled video signals, and present a maximum-likelihood dictionary learning based reconstruction algorithm for DCVS, in which both the correlation and sparsity constraints are included in a new probabilistic model. Moreover, the signal recovery in our algorithm is performed during the process of dictionary learning, instead of being employed as an independent task. Experimental results show that our proposal compares favorably with other existing methods, with 0.1–3.5 dB improvements in the average PSNR, and a 2–9 dB gain for non-key frames when key frames are subsampled at an increased rate.     

Enhanced pipelined architecture of H.264/AVC intra prediction

This paper presents a high-performance encoder for H.264/AVC intra prediction. Due to long data dependency loop of intra 4×4 prediction and complex algorithms, improving encoding speed turns into a stumbling block we have to face. To solve this problem, we first propose a pipelined method in and between macro blocks with new block processing order to accelerate the encoding speed. Benefiting from the pipelined method, reconstructed pixels of up-right blocks are available for two blocks in a macro block which could not take advantage of reconstructed pixels of up-right blocks in JM. So diagonal down left mode and vertical left mode are effective for these two blocks, which ultimately achieves a better bit-rate. Secondly, all 4×4 mode formula sharing method is proposed to reduce the redundancy of predicting formulas. Thirdly, streamlined reconstruction method is applied to improve the performance of reconstruction. CAVLC encoder with three parallel units is proposed to improve entropy coding speed significantly. As a result, it takes 268 cycles to encode a macro block. The experimental results indicate that synthesized into a 0.18 µm CMOS cell library, the new architecture only requires about 238K gates and it is able to encode 1080pHD video sequences at 30 frames per second (fps), at the operating frequency of 56 MHz.     

Exploiting quantization and spatial correlation in virtual-noise modeling for distributed video coding

Aiming for low-complexity encoding, video coders based on Wyner–Ziv theory are still unsuccessfully trying to match the performance of predictive video coders. One of the most important factors concerning the coding performance of distributed coders is modeling and estimating the correlation between the original video signal and its temporal prediction generated at the decoder.One of the problems of the state-of-the-art correlation estimators is that their performance is not consistent across a wide range of video content and different coding settings. To address this problem we have developed a correlation model able to adapt to changes in the content and the coding parameters by exploiting the spatial correlation of the video signal and the quantization distortion.In this paper we describe our model and present experiments showing that our model provides average bit rate gains of up to 12% and average PSNR gains of up to 0.5 dB when compared to the state-of-the-art models. The experiments suggest that the performance of distributed coders can be significantly improved by taking video content and coding parameters into account.     

A DOP feedback controlling multi-stage electrical PMD compensator in digital coherent receiver

We proposed a degree of polarization (DOP) controlling multi-stage electrical polarization mode dispersion (PMD) compensator in digital coherent receiver. The compensator is modulation format independent and can mitigate both first order and higher order PMD. We evaluated this PMD compensator in both 100-Gb/s 16-QAM and QPSK signal transmission systems with 15 ps and 20 ps average differential group delay (DGD) respectively. The results show that, for both two cases, less than 0.2 dB optical signal to noise ratio (OSNR) penalty at 1e^?3 symbol error rate (SER) can be achieved after 4-stage PMD compensation.     

Suppression of optical beat interference-noise in orthogonal frequency division multiple access-passive optical network link using self-homodyne balanced detection

A new technique, which reduces optical beat interference (OBI) noise in orthogonal frequency division multiple access-passive optical network (OFDMA-PON) links, is proposed. A self-homodyne balanced detection, which uses a single laser for the optical line terminal (OLT) as well as for the optical network unit (ONU), reduces OBI noise and also improves the signal to noise ratio (SNR) of the discrete multi-tone (DMT) signal. The proposed scheme is verified by transmitting quadrature phase shift keying (QPSK)-modulated DMT signal over a 20-km single mode fiber. The optical signal to noise ratio (OSNR), that is required for BER of 10⁻⁵, is reduced by 2 dB in the balanced detection compared with a single channel due to the cancellation of OBI noise in conjunction with the local laser.     

An automatic region-based video sequence codec based on fractal compression

In order to improve the performance of fractal video coding, we explore a novel fractal video sequences codec with automatic region-based functionality. To increase the quality of decoding image, intra frame coding, deblocking loop filter and sub-pixel block matching are applied to the codec. An efficient searching algorithm is used to increase the compression ratio and encoding speed. Automatic region-based fractal video sequences coding reduces coding stream greatly. Experimental results indicate that the proposed algorithm is more robust, and provides much less encoding time and bitrate while maintaining the quality of decompression image than the conventional CPM/NCIM method and other related references. We compare the proposed algorithm with three algorithms in Refs. [24], [25], [26], and the results of all these four algorithms are compared with H.264. The bitrate of the proposed algorithm is decreased by 0.11% and the other algorithms are increased by 4.29%, 6.85% and 11.62%, respectively. The average PSNR degradations of the four algorithms are 0.71 dB, 0.48 dB, 0.48 dB and 0.75 dB. So the bitrate of the proposed algorithm is decreased and the other algorithms are increased. At the meantime the compression time is reduced greatly, about 79.19% on average. The results indicate that, on average, the proposed automatic region-based fractal video sequences coding system can save compression time 48.97% and bitrate 52.02% with some image quality degradation in comparison with H.264, since they are all above 32 dB and the human eyes are insensitive to the differences.     

A digital predistortion assisted hybrid supply modulator for envelope tracking power amplifiers

In this paper, a novel digital predistortion assisted supply modulator is presented. The proposed modulator is suitable for envelope tracking power amplifiers. In this topology, a digitally controlled linear power amplifier is used to compensate the switching noise ripples of the switching modulator. The proposed structure is evaluated with a 0.18 µm CMOS process technology. The results show up to 9% static efficiency improvement in comparison with previous one-phase and two-phase architectures. It is shown that for a 5 MHz WiMAX signal with a 6.7 dB PAPR at 26.8 dBm output power, a maximum average efficiency of 73.5% is achieved in the proposed design.     

Fast motion estimation for surveillance video compression

In this article, novel approaches to perform efficient motion estimation specific to surveillance video compression are proposed. These includes (i) selective (ii) tracker-based and (iii) multi-frame-based motion estimation. In selective approach, motion vector search is performed for only those frames that contain some motion activity. In another approach, contrary to performing motion estimation on the encoder side, motion vectors are calculated using information of a surveillance video tracker. This approach is quicker but for some scenarios it degrades the visual perception of the video compared with selective approach. In an effort to speed up multi-frame motion estimation, we propose a fast multiple reference frames-based motion estimation technique for surveillance videos. Experimental evaluation shows that significant reduction in computational complexity can be achieved by applying the proposed strategies.     

Hardware implementation of a spatio-temporal average filter for real-time denoising of fluoroscopic images

An electronic system for the real-time denoising of fluoroscopic images is proposed in this paper. Fluoroscopic devices use X-rays to obtain real-time moving images of patients and support many surgical interventions and a variety of diagnostic procedures. In order to avoid risks for the patient, X-ray intensity has to be kept acceptably low during the clinical applications. This implies that fluoroscopic images are corrupted by large quantum noise (Poisson-distributed). Real-time noise reduction can offer a better visual perception to doctors and possible further reductions of the dose.The proposed circuit implements a spatio-temporal filter optimized for the removal of the quantum noise while preserving video edges and the prompt response of the image to the introduction of new features in the field. The filter incorporates information on the dependence of the standard deviation of the noise on the local brightness of the image and performs a conditioned average operation.The proposed circuit is implemented on FPGA (Field Programmable Gate Array) device allowing the real time elaboration of video streams composed by frames with 1024×1024 pixel and uses an external DDR2 (Double Data Rate 2) memory for the storage and the reuse of the fluoroscopic frames needed by the filter.When implemented on StratixIV-GX70 FPGA the circuit is able to process up to 49 fps (frames per second) while using 80% of the logic resources of the FPGA.