Direction-adaptive fixed length discrete cosine transform framework for efficient H.264/AVC video coding

The 2D-discrete cosine transform (2D-DCT) is one of the popular transformation for video coding. Yet, 2D-DCT may not be able to efficiently represent video data with fewer coefficients for oblique featured blocks. To further improve the compression gain for such oblique featured video data, this paper presents a directional transform framework based on direction-adaptive fixed length discrete cosine transform (DAFL-DCT) for intra-, and inter-frame. The proposed framework selects the best suitable transform mode from eight proposed directional transform modes for each block, and modified zigzag scanning pattern rearranges these transformed coefficients into a 1D-array, suitable for entropy encoding. The proposed scheme is analysed on JM 18.6 of H.264/AVC platform. Performance comparisons have been made with respect to rate-distortion (RD), Bjontegaard metrics, encoding time etc. The proposed transform scheme outperforms the conventional 2D-DCT and other state-of-art techniques in terms of compression gain and subjective quality.     

基于三维DCT的彩色图象自适应水印算法

本文提出了一种基于3D-DCT的彩色图象自适应水印算法.证实了RGB彩色图象的3D-DCT比2D-DCT具有更好的能量汇聚性质并因此具有更大的感觉容量,从而允许嵌入更强的水印信号.在此基础上,提出了利用人眼彩色视觉特性来自适应控制水印嵌入强度的方法.实验证明该算法较好地平衡了隐形水印的不可见性和稳健性之间的矛盾,所隐藏的水印对常规性攻击,如JPEG压缩、加性噪声、图象滤波、彩色变化和亮度/对比度变化等,具有很好的抵抗能力.     

一种基于DCT系数重组的降参考3D视频质量评价方法

针对3D视频质量评价,提出了一种基于离散余弦变 换(DCT)系数重组的降参考质量评价方法。方法主要 包括4D数据集构造、DCT变换与重组和降参考(RR)质量评价3个阶段。在4D数据集构造阶段 ,通过联合视 频的空间域、视点域和时间域信息构造包含3D视频全部信息的4D数据集;在DCT变换与重 组阶段,首 先对数据集进行DCT变换,然后筛选复杂度较高的DCT系数进行重组,得到能够表征3D视 频质量的重 组系数集;在RR质量评价阶段,首先采用广义高斯分布(GGD)函数对重组后DCT系数集的每 个子带进行建模, 然后利用系数距离函数和频率比距离函数评估3D视频质量。实验结果表明,本文提出的方 法与主观评价结果有较好的相关性,符合人类视觉系统(HVS)。     

基于DCT系数统计特性的HEVC视频双压缩检测算法

功能强大和使用简易的视频编辑软件可能会使数字视频遭受到各种不同形式的篡改,视频的真实性和完整性无法得到保证。双压缩是视频篡改的必要条件,双压缩检测则是视频取证的重要辅助手段。通过分析压缩过程中由量化误差引起的离散余弦变换(DCT)系数变化,提出了一种不同量化参数下的高效视频编码(HEVC)视频双压缩检测算法,利用DCT系数直方图和相邻DCT系数对奇偶组合统计特性构造22维联合特征集,最后将特征集用支持向量机(SVM)进行分类识别。实验结果证明了本文算法的有效性。     

A 3D-DCT video encoder using advanced coding techniques for low power mobile device

The three-dimensional discrete cosine transform (3D-DCT) has been researched as an alternative to existing dominant video standards based on motion estimation and compensation. Since it does not need to search macro block for inter/intra prediction, 3D-DCT has great advantages for complexity. However, it has not been developed well because of poor video quality while video standards such as H.263(+) and HEVC have been blooming. In this paper, we propose a new 3D-DCT video coding as a new video solution for low power mobile technologies such as Internet of Things (IoT) and Drone. We focus on overcoming drawbacks reported in previous research. We build a complete 3D-DCT video coding system by adopting existing advanced techniques and devising new coding algorithms to improve overall performance of 3D-DCT. Experimental results show proposed 3D-DCT outperforms H.264 low power profiles while offering less complexity. From GBD-PSNR, proposed 3D-DCT provides better performance by average 4.6 dB.     

一种高清视频低延时远程传输方法

针对远程高清视频传输延迟问题,提出了一种改进的DCT系数量化方法.此方法通过一个自适应取样函数对DCT压缩量化系数进行了分块取样,再对DCT系数重构量化后以百兆以太网的IP包进行实时压缩传输,且接收端通过IDCT变换进行解压,并加入均值为零的噪声处理,解决了图像压缩的块效应问题,从而实现远程实时传输高清视频,满足了民用中对高清视频远程实时传输的要求.     

Three-dimensional steerable discrete cosine transform with application to 3D image compression

This work introduces the three-dimensional steerable discrete cosine transform (3D-SDCT), which is obtained from the relationship between the discrete cosine transform (DCT) and the graph Fourier transform of a signal on a path graph. One employs the fact that the basis vectors of the 3D-DCT constitute a possible eigenbasis for the Laplacian of the product of such graphs. The proposed transform employs a rotated version of the 3D-DCT basis. We then evaluate the applicability of the 3D-SDCT in the field of 3D medical image compression. We consider the case where we have only one pair of rotation angles per block, rotating all the 3D-DCT basis vectors by the same pair. The obtained results show that the 3D-SDCT can be efficiently used in the referred application scenario and it outperforms the classical 3D-DCT.

     

Video saliency detection incorporating temporal information in compressed domain

Saliency detection is widely used to pick out relevant parts of a scene as visual attention regions for various image/video applications. Since video is increasingly being captured, moved and stored in compressed form, there is a need for detecting video saliency directly in compressed domain. In this study, a compressed video saliency detection algorithm is proposed based on discrete cosine transformation (DCT) coefficients and motion information within a visual window. Firstly, DCT coefficients and motion information are extracted from H.264 video bitstream without full decoding. Due to a high quantization parameter setting in encoder, skip/intra is easily chosen as the best prediction mode, resulting in a large number of blocks with zero motion vector and no residual existing in video bitstream. To address these problems, the motion vectors of skip/intra coded blocks are calculated by interpolating its surroundings. In addition, a visual window is constructed to enhance the contrast of features and to avoid being affected by encoder. Secondly, after spatial and temporal saliency maps being generated by the normalized entropy, a motion importance factor is imposed to refine the temporal saliency map. Finally, a variance-like fusion method is proposed to dynamically combine these maps to yield the final video saliency map. Experimental results show that the proposed approach significantly outperforms other state-of-the-art video saliency detection models.     

Visibility of wavelet quantization noise

The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression, measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r2^-λ, where r is the display visual resolution in pixels/degree, and λ is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a “perceptually lossless” quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes     

Hash key-based video encryption scheme for H.264/AVC

An improved H.264/AVC comprehensive video encryption scheme is proposed. In the proposed scheme, the intra-prediction mode, motion vector difference, and quantization coefficients are encrypted. A novel hierarchical key generation method is likewise proposed, in which the encryption keys are generated based on the cryptographic hash function. Generated frame keys are consistent with the corresponding frame serial numbers, which can ensure frame synchronization in the decrypting process when frame loss occurs. This function provides the property that our scheme is secure against some special attacks for video, such as the frame regrouping attack and frame erasure attack. Our method not only avoids the distribution of encryption keys, but also increases the security. Experimental results show that the proposed scheme is efficient in computing, the encryption process does not affect the compression ratio greatly, and the encryption/decryption process hardly affects the video quality.     

Post‐processing of 3D Video Extension of H.264/AVC for a Quality Enhancement of Synthesized View Sequences

Since July of 2012, the 3D video extension of H.264/AVC has been under development to support the multi‐view video plus depth format. In 3D video applications such as multi‐view and free‐view point applications, synthesized views are generated using coded texture video and coded depth video. Such synthesized views can be distorted by quantization noise and inaccuracy of 3D wrapping positions, thus it is important to improve their quality where possible. To achieve this, the relationship among the depth video, texture video, and synthesized view is investigated herein. Based on this investigation, an edge noise suppression filtering process to preserve the edges of the depth video and a method based on a total variation approach to maximum a posteriori probability estimates for reducing the quantization noise of the coded texture video. The experiment results show that the proposed methods improve the peak signal‐to‐noise ratio and visual quality of a synthesized view compared to a synthesized view without post processing methods.     

基于神经网络的量化参数预测研究

在视频有损压缩编码中,量化是为达到压缩视频的目的,将原信号值映射到较小取值范围的过程。一个合适的量化参数(QP)可以在增加压缩效率的同时平衡视频质量和编码复杂度。现有的码率控制算法对运动剧烈及存在场景切换的连续帧控制不精确,视频PSNR值波动大。本文提出一种基于神经网络的视频量化参数选择,利用已编码帧信息对当前帧的量化参数计算进行调整。神经网络模型选取当前帧的目标比特、当前帧的MAD和前一帧编码的QP和实际比特数作为输入,输出值经过反归一化及取整处理对视频进行量化。实验表明,编码时使用该方法进行与H.264/AVC的标准参考软件JM14.2相比,在保证码率精确度和平均PSNR值基本不变的情况下,减小了PSNR的波动。     

3D scanning-based compression technique for digital hologram video

In this paper, we proposed an efficient coding method for digital hologram video using a three-dimensional (3D) scanning method and two-dimensional (2D) video compression technique. It consists of separation of the captured 3D image into R, G, and B color space components, localization by segmenting the fringe pattern in to M×N [pixel²], frequency-transform by 2D discrete cosine transform (2D DCT), 3D-scanning the segments to form a video sequence, classification of coefficients, and hybrid video coding with H.264/AVC, differential pulse code modulation (DPCM), and lossless coding method. The experimental results with this method showed that the proposed method has compression ratios of 8–16 times higher than the previous researches. Thus, we expect it to contribute to reduce the amount of digital hologram data for communication or storage.     

Motion-compensated wavelet transform coder for very low bit-rate visual telephony

This paper proposes a new motion-compensated wavelet transform video coder for very low bit-rate visual telephony. The proposed coder sequentially employs: (1) selective motion estimation on the wavelet transform domain, (2) motion-compensated prediction (MCP) of wavelet coefficients, and (3) selective entropy-constrained vector quantization (ECVQ) of the resultant MCP errors. The selective schemes in motion estimation and in quantization, which efficiently exploit the characteristic of image sequences in a visual telephony, considerably reduce the computational burden. The coder also employs a tree structure encoding to represent efficiently which blocks were encoded. In addition, in order to reduce the number of ECVQ codebooks and the image dependency of their performance, we introduce a preprocessing of signals which normalizes input vectors of ECVQ. Simulation results show that our video coder provides good PSNR (peak-to-peak signal-to-noise ratio) performance and efficient rate control.     

An Improved Floating-to-Fixed-Point Conversion Scheme for DCT Quantization Algorithm

Conventional fixed-point implementation of the DCT coefficients quantization algorithm in video compression may result in deteriorated image quality. The paper investigates this problem and proposes an improved floating-to-fixed-point conversion scheme. With a proper scaling factor and a new-established look-up table, the proposed fixed-point scheme can obtain bit-wise consistence to the floating-point realization. Experimental results verify the validity of the proposed method.     

自适应量化索引调制及其信道编码的信息隐藏技术的研究

在信息隐藏通信时,对JPEG-2000小波多级分解并在嵌入块编码中根据不同级的LL-HH分组系数引入自适应量化索引调制(AQIM),同时结合信道编码技术可以有效地实现指纹节点数据的信息隐藏和安全传输技术.通过实验可知,低码率时,与QIM隐藏技术相比,本系统有效地提高了恢复指纹图像的PSNR,同时降低了系统的BER,表明该系统恢复的图像具有更好的感官质量和更强的鲁棒性.     

Foveation embedded DCT domain video transcoding

Video transcoding is a key technology to support video communications over heterogeneous networks. Although quite a bit of research effort has been made in video transcoding due to its wide applications, most video transcoding techniques proposed in the literature are optimized based on the simple mean squared error (MSE) metric which does not correlate well with the human visual perception. In this paper, foveation, a property of the HVS, is exploited in video transcoding. The proposed foveation embedded DCT domain video transcoding can reduce the bit rate without compromising visual quality or achieve better subjective quality for a given bit rate by shaping the compression distortion according to the foveated contrast sensitivity function of the HVS. In addition, fast algorithms for video foveation filtering and DCT domain inverse motion compensation are developed, which significantly improve the efficiency of video transcoding.     

一种结合人眼对比度感知特性的彩色图像压缩算法

为了使图像压缩后的效果更加符合人眼感知特性,提出了一种结合人眼对比度敏感视觉特性的图像压缩算法。算法首先结合视觉特性和图像变换域频谱系数特征,提出一种图像的角频率的计算方法,并依据计算的角频率提出一种人眼觉察图像最小误差阈值的计算方法;然后以此阈值作为量化步长,提出一种图像变换域频谱系数的量化方法;最后采用霍夫曼编码算法进行编解码,实现图像的压缩。并对三幅彩色图像进行了仿真实验,结果表明:与JPEG技术相比,三幅彩色图和各分量图的平均压缩比、PSNR和SSIM依次提高了10.4807%、6.9879%和2.6494%。表明提出的结合人眼视觉特性的图像压缩算法是一种较好的、有实用价值的压缩算法。     

Novel Efficient De-blocking Method for Highly Compressed Images

Due to coarse quantization, block-based discrete cosine transform（BDCT） compression methods usually suffer from visible blocking artifacts at the block boundaries. A novel efficient deblocking method in DCT domain is proposed. A specific criterion for edge detection is given, one-dimensional DCT is applied on each row of the adjacent blocks and the shifted block in smooth region, and the transform coefficients of the shifted block are modified by weighting the average of three coefficients of the block. Mean square difference of slope criterion is used to judge the efficiency of the proposed algorithm. Simulation results show that the new method not only obtains satisfactory image quality, but also maintains high frequency information.     

Visual saliency guided video compression algorithm

Recently Saliency maps from input images are used to detect interesting regions in images/videos and focus on processing these salient regions. This paper introduces a novel, macroblock level visual saliency guided video compression algorithm. This is modelled as a 2 step process viz. salient region detection and frame foveation. Visual saliency is modelled as a combination of low level, as well as high level features which become important at the higher-level visual cortex. A relevance vector machine is trained over 3 dimensional feature vectors pertaining to global, local and rarity measures of conspicuity, to yield probabilistic values which form the saliency map. These saliency values are used for non-uniform bit-allocation over video frames. To achieve these goals, we also propose a novel video compression architecture, incorporating saliency, to save tremendous amount of computation. This architecture is based on thresholding of mutual information between successive frames for flagging frames requiring re-computation of saliency, and use of motion vectors for propagation of saliency values.