基于H.264的无再损帧内编码

为了在改进的H.264上实现无再损帧内编码,该文提出了一种新的基于整数线性规划的优化clip算法及改进算法,解决了H.264多次编码中由当前clip模块和帧内预测运算引入的视频畸变问题,并且改进了现有帧内预测算法的代价函数以确保多次编码时后续编码器预测值与前次编码器预测值一致。实验结果显示,与现有帧内编码算法比较,基于整数线性规划理论的帧内编码算法完全消除了现有算法导致的多次编码时的图像降质现象,在改进的H.264编解码算法中实现了严格视频无再损编码。     

An algorithm for coding video signal based on 3-D wavelet transformation

This paper presents an algorithm for coding video signal based on 3-D wavelet transformation. When the frame order t of a video signal is replaced by order 2, the video signal can be looked as a block in 3-D space. After splitting the block into smaller sub-blocks, imitate the method of 2-D wavelet transformation for images, we can transform the sub-blocks with 3-D wavelet. Most of video signal energy is in the decomposed low-frequency sub-bands. These sub-bands affect the visual quality of the video signal most. Quantizing different sub-bands with different precision and then entropy encoding each sub-band, we can eliminate inter- and intra-frame redundancy of the video signal and compress data. Our simulation experiments show that this algorithm can achieve very good result.     

Complexity-based intra frame rate control by jointing inter-frame correlation for high efficiency video coding

Rate control is of great significance for the High Efficiency Video Coding (HEVC). Due to the high efficiency and low complexity, the R-lambda model has been applied to the HEVC as the default rate control algorithm. However, the video content complexity, which can help improve the code efficiency and rate control performance, is not fully considered in the R-lambda model. To address this problem, an intra-frame rate control algorithm, which aims to provide improved and smooth video quality, is developed in this paper by jointly taking into consideration the frame-level content complexity between the encoded intra frames and the encoded inter frame, as well as the CTU-level complexity among different CTUs in texture–different regions for intra-frame. Firstly, in order to improve the rate control efficiency, this paper introduces a new prediction measure of content complexity for CTUs of intra-frame by jointly considering the inter-frame correlations between encoding intra frame and previous encoded inter frames as well as correlations between encoding intra frame and previous encoded intra frame. Secondly, a frame-level complexity-based bit-allocation-balancing method, by jointly considering the inter-frame correlation between intra frame and previous encoded inter frame, is brought up so that the smoothness of the visual quality can be improved between adjacent inter- and intra-frames. Thirdly, a new region-division and complexity-based CTU-level bit allocation method is developed to improve the objective quality and to reduce PSNR fluctuation among CTUs in intra-frame. In the end, related model parameters are updated during the encoding process to increase rate control accuracy. As a result, as can be seen from the extensive experimental results that compared with the state-of-the-art schemes, the video quality can be significantly improved. More specifically, up to 10.5% and on average 5.2% BD-Rate reduction was achieved compared to HM16.0 and up to 2.7% and an average of 2.0% BD-Rate reduction was achieved compared to state-of-the-art algorithm. Besides, a superior performance in enhancing the smoothness of quality can be achieved, which outperforms the state-of-the-art algorithms in term of flicker measurement, frame and CTU-wise PSNR, as well as buffer fullness.     

H．264视频编码技术研究

H．264作为新一代的视频编码标准,在近年来成为首选的视频标准。为了提高视频编码效率,H．264已采用了许多新技术,但仍面临一些瓶颈问题,影响其编码效率。结合JM8．6从视频编码层出发对H．264的帧间预测、帧内预测、变换及熵编码进行了分析和研究。结合实验分析得出帧内及帧间预测模式的概率,结果说明H．264复杂度和实时性能仍有待进一步的改善。     

An efficient six-parameter perspective motion model for VVC

Tilt and pan camera movements are common in computer games or social media videos. These types of videos contain numerous perspective transforms while today’s video codecs rely on translational and affine motion models for motion compensation. The general perspective motion model with 8 parameters (8PMM) has unreasonably high processing time. In this paper, the eight-parameter perspective transform is simplified into a six-parameter transform to keep the time complexity within an acceptable range while modeling the most relevant transforms. Also, two motion prediction modes, Advanced Perspective Motion Vector Prediction (APMVP) and Perspective Model Merge (PMM), are proposed. The implementation results show an average of 7.0% BD-rate reduction over H.266/VVC Test Model with a maximum of 20% encoding time overhead. The results also show a 71% processing time reduction in comparison to 8PMM while experiencing an average of 5.6% increase in BD-Rate. Much better visual quality is measured through VMAF quality meter.     

基于分块三维小波变换的视频图像序列编码方法的研究

该文给出了一种基于分块三维小波变换的视频图像序列编码方法。将视频图像序列中表示帧序的t坐标代换成z坐标后,可把一视频图像序列看成是三维空间中的体。将视频图像序列分成子块后,仿照二维图像小波变换的方法,将它作三维小波变换。变换后的图像能量主要集中于低频波段,这些波段对该视频图像序列的视觉效果影响最大。将不同波段按不同的精度量化并进行熵编码,可以达到去除帧内和帧间冗余、压缩数据的目的。试验表明,使用这种方法可以达到较好的压缩效果。此方法直观,速度也比较快。     

基于多参考帧的平行立体视频视间编码的实现

Side-by-Side(SbS)是立体视频常用的格式。传统的视频编码方法利用帧内预测或帧间预测对视频进行压缩编码。基于H.264视频压缩编码标准,针对SbS格式的立体视频提出了一种基于多参考帧方式的视间预测编码方法,并在JM测试代码基础上将其实现。实验结果表明,加入视间预测编码后,以很小的PSNR损失为代价,使得SbS视频的压缩效率提高了大约10%～20%。     

Predictive coding of images using an adaptive intra-frame predictor and motion compensation

In this article we present an image predictive coding method using both intra- and inter-frame predictors. The intra-frame predictor is an adaptive FIR filter using the well-known LMS algorithm to track continuously spatial local characteristics of the intensity. The inter-frame predictor is motion-adaptive using a pel-recursive method estimating the displacement vector. Weight coefficients are continuously adapted in order to favor the prediction mode which performs better between intra-frame and motion compensation mode. It is a backwards adaptation which does not necessitate the transmission of an overhead information. Neither the weight coefficients nor displacement vectors are transmitted. Apart from the quantized prediction error, it may be necessary to transmit the detection of a discontinuity of the displacement vector. For the examined image sequence a significant improvement is obtained in comparison with only adaptive intra-frame or only motion compensation mode. We give and discuss the extension of a known adaptive quantizer for 2D signals. A crucial problem in predictive coding, particularly with adaptive techniques, is the sensitivity to transmission errors. A method ensuring the self-adjustment of the decoder in the presence of transmission errors, which do not affect the pixel synchronization, is proposed for the intra-frame mode. Neither overhead information nor error-correcting codes are needed.     

一种基于多参考帧的平行立体视频视间编码实现方法

Side-by-Side（SbS）是立体视频常用的格式。传统的视频编码方法利用帧内预测或帧间预测对视频进行压缩编码。本文基于H.264视频压缩编码标准,针对SbS格式的立体视频提出了一种基于多参考帧方式的视间预测编码方法,并在JM测试代码基础上将其实现。实验结果表明,加入视间预测编码后,以很小的PSNR损失为代价,使得SbS视频的压缩效率提高了大约10%至20%。     

基于多分支网络的深度图帧内编码单元快速划分算法

3维高效视频编码(3D-HEVC)标准是最新的3维(3D)视频编码标准,但由于其引入深度图编码技术导致编码复杂度大幅增加。其中,深度图帧内编码单元(CU)的四叉树划分占3D-HEVC编码复杂度的90%以上。对此,在3D-HEVC深度图帧内编码模式下,针对CU四叉树划分复杂度高的问题,该文提出一种基于深度学习的CU划分结构快速预测方案。首先,构建学习深度图CU划分结构信息的数据集;其次,搭建预测CU划分结构的多分支卷积神经网络(MB-CNN)模型,并利用构建的数据集训练MB-CNN模型;最后,将MB-CNN模型嵌入3D-HEVC的测试平台,通过直接预测深度图帧内编码模式下CU的划分结构来降低CU划分复杂度。与标准算法相比,编码复杂度平均降低了37.4%。实验结果表明,在不影响合成视点质量的前提下,该文所提算法有效地降低了3D-HEVC的编码复杂度。     

Deep chroma prediction of Wyner–Ziv frames in distributed video coding of wireless capsule endoscopy video

Compression of captured video frames is crucial for saving the power in wireless capsule endoscopy (WCE). A low complexity encoder is desired to limit the power consumption required for compressing the WCE video. Distributed video coding (DVC) technique is best suitable for designing a low complexity encoder. In this technique, frames captured in RGB colour space are converted into YCbCr colour space. Both Y and CbCr representing luma and chroma components of the Wyner–Ziv (WZ) frames are processed and encoded in existing DVC techniques proposed for WCE video compression. In the WCE video, consecutive frames exhibit more similarity in texture and colour properties. The proposed work uses these properties to present a method for processing and encoding only the luma component of a WZ frame. The chroma components of the WZ frame are predicted by an encoder–decoder based deep chroma prediction model at the decoder by matching luma and texture information of the keyframe and WZ frame. The proposed method reduces the computations required for encoding and transmitting of WZ chroma component. The results show that the proposed DVC with a deep chroma prediction model performs better when compared to motion JPEG and existing DVC systems for WCE at the reduced encoder complexity.     

Adaptive Scanning for H.264/AVC Intra Coding

In this letter, an adaptive scanning that improves intra coding efficiency in the H.264/AVC standard is proposed. The proposed adaptive scanning utilizes the prediction directions (modes) that include the horizontal and vertical edge information in a block. Depending on the prediction directions, the proposed method uses three scanning methods: zigzag scanning, horizontal scanning, and vertical scanning. In the proposed method, horizontal and vertical scanning are used in vertical and horizontal prediction modes, respectively, and the normal zigzag scanning in the H.264 standard is used in all other intra prediction modes. The proposed method reduces the bit rate by approximately 2.5% compared with H.264/AVC, without the degradation of video quality.     

MPEG-4自然视频编码技术

对MPEG－4自然视频编码的关键技术作了详细的分析和阐述。首先介绍MPEG－4频语法结构，并对视频编码的框架概要分析。接着分析了自然视频编码中涉及到的关键技术，包括：VOP的产生；二值和灰度级α平面的编码技术；运动估计和补偿方法；纹理编码；基于对象的时间分级和空间分级；MPEG－4提供的再同步和各种错误掩盖，刷新方法，精 编码技术和零树小波基的静止图像编码技术。指出MPEG－4和MPEG－1，MPEG－2等标准的异同，突出MPEG－4的三个主要特点。最后给出MPEG－4技术在网络视频传输中的应用，并给出测试和分析。     

Adaptive lossless compression of skeleton sequences

The increasing importance of skeleton information in surveillance big data feature analysis demands significant storage space. The development of an effective and efficient solution for storage is still a challenging task. In this paper, we propose a new framework for the lossless compression of skeleton sequences by exploiting both spatial and temporal prediction and coding redundancies. Firstly, we propose a set of skeleton prediction modes, namely, spatial differential-based, motion vector-based, relative motion vector-based, and trajectory-based skeleton prediction mode. These modes can effectively handle both spatial and temporal redundancies present in the skeleton sequences. Secondly, we further enhance performance by introducing a novel approach to handle coding redundancy. Our proposed scheme is able to significantly reduce the size of skeleton data while maintaining exactly the same skeleton quality due to lossless compression approach. Experiments are conducted on standard surveillance and Posetrack action datasets containing challenging test skeleton sequences. Our method obviously outperforms the traditional direct coding methods by providing an average of 73% and 66% bit-savings on the two datasets.     

A joint source and channel coding algorithm for error-resilient SPIHT-coded video bitstreams

We propose an analytical rate-distortion optimized joint source and channel coding algorithm for error-resilient scalable encoded video for lossy transmission. A video is encoded into multiple independent substreams to avoid error propagation and is assigned forward error correction (FEC) codes and source bits using Lagrange optimization. Our method separates video coding and packetization into different tiers which can be easily incorporated into any coding structure that generates a set of independent compressed bit-streams. To demonstrate the performance, we use the 2-state Markov model to describe the burst loss channel and Reed-Solomon codes as forward error correction codes. Simulation results show that the proposed channel incorporated rate-distortion optimization approach have better performance.     

SVM based approach for complexity control of HEVC intra coding

The High Efficiency Video Coding (HEVC) is adopted by various video applications in recent years. Because of its high computational demand, controlling the complexity of HEVC is of paramount importance to appeal to the varying requirements in many applications, including power-constrained video coding, video streaming, and cloud gaming. Most of the existing complexity control methods are only capable of considering a subset of the decision space, which leads to low coding efficiency. While the efficiency of machine learning methods such as Support Vector Machines (SVM) can be employed for higher precision decision making, the current SVM-based techniques for HEVC provide a fixed decision boundary which results in different coding complexities for different video content. Although this might be suitable for complexity reduction, it is not acceptable for complexity control. This paper proposes an adjustable classification approach for Coding Unit (CU) partitioning, which addresses the mentioned problems of complexity control. Firstly, a novel set of features for fast CU partitioning is designed using image processing techniques. Then, a flexible classification method based on SVM is proposed to model the CU partitioning problem. This approach allows adjusting the performance-complexity trade-off, even after the training phase. Using this model, and a novel adaptive thresholding technique, an algorithm is presented to deliver video encoding within the target coding complexity, while maximizing the coding efficiency. Experimental results justify the superiority of this method over the state-of-the-art methods, with target complexities ranging from 20% to 100%.     

Early merge mode decision for texture coding in 3D-HEVC

As the upcoming 3D video coding standard, high efficiency video coding (HEVC) based 3D video coding (3D-HEVC) has been drafted. In 3D-HEVC, the computational complexity of mode decision process is significantly high due to exhaustive modes’ checks for coding units (CU) derived from recursive quad-tree partitioning. In this paper, we propose an early merge mode decision method for complexity reduction of dependent texture views. First, inter-view correlation and hierarchical depth correlation of coding modes are separately analyzed for B frame and P frame. Then, conditions to early determine merge mode coded CUs are derived based on the correlations. All of the early determined CUs only check merge modes in the mode decision process, which brings considerable complexity reduction. Experimental results demonstrate that the proposed method can achieve average 20.4% of encoding time saving for dependent texture views with negligible rate distortion performance loss.     

基于多时-空相关的AVS2快速帧间预测算法

针对新一代视频标准AVS2引进四叉树分割、多参考帧等技术而带来的帧间预测复杂度增加的问题,提出一种基于多时-空相关的快速帧间预测算法.该算法利用上下层相邻编码单元(Coding Unit,CU)和空时域相邻CU在预测模式选择上的相关性,计算当前CU的模式复杂度,根据复杂度为当前CU分配合适的候选预测模式;同时利用相邻预测单元(Prediction Unit,PU)在参考帧选择上的相关性,计算当前PU的参考帧索引,根据索引为当前PU分配合适的候选参考帧.实验表明,该算法在BD-Rate(Bjontegaard delta bit rate)增加1.22％,BD-PSNR(Bjontegaard delta peak signal-to-noise rate)降低0.04 dB的前提下,平均减少47.54％的编码时间.     

三角形网格基活动图像编码研究——基本框架和I帧编码

本文结合实验结果,深入讨论了三角形网格基活动图像编码方法的基本框架和帧内编码问题。文中全面比较了DTM+MD的帧内编码方法和JPEG方法的性能,表明采用DTM+MD作帧内编码具有更好的主客观质量。