一种基于残差系数的快速编码算法

当前视频编码标准有着较高的编码效率,然而也较多地提高了编码复杂度,因此提高编码速度具有很重要的意义。根据残差系数的分布特征,该文提出了一种基于残差的快速编码算法。该算法首先根据Inter1616或者Inter88编码得到的残差系数进行假设检验,根据假设检验的结果来预测可能的编码模式集合;然后根据DCT系数的分布特征分别计算出全零块,11子块,22子块和33子块的判决条件,从而避免44子块中全部或者部分系数的DCT,Q,IQ,IDCT运算。实验证明,该文算法的编码速度要显著快于其它算法,同时编码效率的损失也很小。     

基于拉普拉斯分布模型的快速DCT算法

为提高编码效率,通过分析残差系数在空域和DCT域均符合拉普拉斯分布后,提出一种快速DCT算法.该算法能够在DCT之前对每个量化DCT系数进行零值预判而节省DCT计算.通过头肩序列的实验表明新算法在不降低图像质量的条件下,其整体运算复杂度优于常规算法.     

H.264/AVC中变换量化模块的可重构设计

基于H.264/AVC视频编码标准,完成编码模块中的整数OCT/Q模块可重构IP核的优化设计.在硬件开销改变不大的情况下,利用可重构理论,提炼出其核心部件即可重构处理元,在同种电路结构上实现变换量比(DCT/Q)和反变换反量比(IDCT/IQ)的功能,满足高清视频实时编解码要求.     

H．264整数DCT的FPGA实现

H.264整数DCT变换算法有助于减少计算复杂度,提高编码速度,进一步提高视频或图像的压缩效率。分析H.264整数DCT变换的快速算法及其实现原理,并提出一种用来具体实现一个4×4块的DCT变换的结构;同时给出用VHDL语言实现4×4块DCT变换的内部模块的源代码和仿真波形。仿真结果表明用该算法可快速实现一个4×4块的整数DCT变换。提出一种切实可行的用于H.264整数DCT变换的结构,该结构可完全用硬件电路快速实现;对于用FPGA实现H.264整数DCT变换做了一次实践性的尝试,对深入理解H.264整数DCT变换及其算法的具体实现具有一定的实践意义。     

高清实时视频流脆弱性数字水印技术研究

为解决高清实时视频流完整性验证问题,文章提出了一种H.264脆弱性数字水印算法,并基于该算法提出了认证方案。通过对水印特征的分析,提出在H.264视频编码时根据I帧的低频DCT量化系数及密钥生成水印信息,嵌入到I帧的高频DCT量化系数中及P帧的DCT量化系数中,并在视频的解码阶段进行检测及验证,水印提取不需要原始视频的参与,属于盲检测。实验结果表明,该文中所提出的算法及验证方案对H.264视频的图像质量、输出码率及编码速度影响较小,并能有效的检测各类攻击,具有较强的实用性及有效性。     

H.263编码中DCT在定点DSP上的实现

简要介绍了H.263编码标准及H.263编码采用的正交变换编码离散余弦变换。文中着重讨论了DCT算法的定点化,并根据TMS320C6201DSP的特点对IDCT的算法进行了改进。最后采用DSP汇编语言实现DCT快速算法。     

基于ADSP—BF533的H．264DCT变换及量化的优化实现

根据ITU-T提出的H.264视频编解码标准,对JM算法及TI Blackfin 533 DSP自身特点进行了分析,将标准中编码采用的整数离散余弦变换(DCT)、量化,解码采用的反DCT变换、反量化的JM算法成功移植到DSP上面,同时根据DSP的特点进行软硬件优化,达到了较好效果。     

基于H.264误差漂移补偿的鲁棒性视频水印算法

针对现有基于H.264的视频水印算法存在误差漂移的问题,在分析了误差漂移产生原因的基础上,提出了一种抑制误差漂移的鲁棒性视频水印新算法.通过调制H.264编码中Ⅰ帧量化后的4 ×4 DCT系数来实现水印的嵌入,并对帧内预测量化后满足特定条件的DCT子块的最后一行、列进行补偿和对帧间预测进行补偿,有效地抑制了帧内、帧间误差漂移.另外,该算法结合CAVLC编码来调制量化后的DCT残差系数,使整体码流变动较小,并且算法能够根据不同视频序列自适应地调节嵌入容量及嵌入位置,具有较好的灵活性和鲁棒性.在水印提取过程中,不需要原始视频的参与,即可实现盲提取.仿真实验结果表明,该算法在具有良好不可见性的前提下,对压缩码率影响较小,能够较好地抵抗噪声、帧剪切、重编码等攻击.     

MPEG-4像素压缩模块的DSP实现

文章在TMS320C6204定点DSP芯片上实现了MPEG-4像素压缩模块的优化.重点讨论了一种快速的DCT/IDCT算法在DSP上的实现,并针对其中最耗时的DCT/IDCT、量化/反量化算法做了软件优化,有效的降低了整个模块的运行时钟数.实验结果表明本文的算法和优化结果都取得了良好的效果.     

一种应用于指纹识别系统的指纹图像压缩算法

针对应用于指纹识别系统中指纹图像的压缩编码问题,提出了一种改进的基于四叉树分类的网格编码量化(QTCQ)的指纹图像压缩算法.该算法对小波变换后的高频系数采用2×2的DCT变换进一步集中能量,并对变换后的系数进行系数重排以使得高频子带内的重要系数集中于相应子带的低频位置,再通过基于四叉树的网格编码量化进行量化编码.仿真结果表明,该算法比WSQ和JPEG2000等均具有更好的压缩性能.     

一种改进的基于DCT的语音增强算法

提出一种改进的基于离散余弦变换的语音增强算法。在信噪比较低时,传统的基于离散余弦变换的语音增强算法效果较好,能较大幅度地提高信号的信噪比;而当信噪比高时,利用这种方法会滤掉一些有用的信号成份。新算法首先计算出所有高阶离散余弦变换系数对应的时域信号中语音信号出现的可能性大小,然后根据某个阈值计算是否在估计噪声信号绝对值的均方差时保留该系数。实验结果表明在含噪语音信号的信噪比高于10dB时,新算法较传统的基于离散余弦变换的算法具有较好的性能。     

Utilizing neighborhood coefficient correlation: a new image watermarking technique robust to singular and hybrid attacks

A new blind digital image watermarking algorithm with watermark embedded in discrete cosine transform (DCT) coefficients is presented in this paper. The proposed scheme exploits correlation between DCT coefficients in neighborhood blocks for embedding. The watermark is embedded by modifying two DCT coefficients, one pertaining to a block in which watermark bit (0 or 1) is to be embedded and the other corresponding to the selected neighborhood block. Both the selected coefficients are modified by a modification factor so that the difference between the pair of coefficients is brought to a predefined zone. This difference between two DCT coefficients is used to extract watermark. The proposed technique has been tested for different attacks like JPEG compression, rotation, cropping, filtering, gaussian noise, salt and pepper noise, histogram equalization etc. It has been observed that the scheme is highly robust not only for the above mentioned attacks used singularly, but also for different possible combinations of simultaneous attacks. A comparison of the proposed technique with some state of art existing algorithms reveals that our scheme provides better results in terms of quality of watermarked images, payload and robustness.     

图像的自嵌入及窜改的检测和恢复算法

提出一种图像自嵌入的水印算法.它将一个图像的主要内容嵌入该图像自身之中.该算法不仅能检测和定位对图像的窜改,而且能恢复被损坏的图像内容.算法的基本思路是把一个图像块的主要DCT系数经过量化、编码和加密后,嵌入另一个图像块的最低位之中.依据大量图像DCT量化系数的统计性质,本文仔细设计了主要DCT系数的编码表,使它既能满足水印负荷的要求,又能保证图像恢复时有较好的质量.分析了水印嵌入块和原图像块间偏移值应该满足的条件和设计方法.该算法为单向、不可逆的,可以抵抗可能的伪造攻击.     

Computation of an odd-length DCT from a real-valued DFT of the samelength

The discrete cosine transform (DCT) is often computed from a discrete Fourier transform (DFT) of twice or four times the DCT length. DCT algorithms based on identical-length DFT algorithms generally require additional arithmetic operations to shift the phase of the DCT coefficients. It is shown that a DCT of odd length can be computed by an identical-length DFT algorithm, by simply permuting the input and output sequences. Using this relation, odd-length DCT modules for a prime factor DCT are derived from corresponding DFT modules. The multiplicative complexity of the DCT is then derived in terms of DFT complexities     

Highly-compacted DCT coefficients

In this paper highly-compacted DCT coefficients (HDCT) are presented. This compactness is achieved by sorting in ascending order the data first, then by applying the Discrete Cosine transform (DCT) to the ordered data. Images are highly correlated. DCT exhibits excellent energy compaction. It will be shown that HDCT has much better energy compactness than the DCT. This has the effect of representing every ordered image with very small number of HDCT coefficients (dimensionality reduction). The compression capabilities of the HDCT are presented. HDCT is also applied to face recognition problem. Simulation results on different databases showed high average success rate of this algorithm compared to other algorithms.     

Data partitioning and coding of DCT coefficients based on requantization for error-resilient transmission of video

In this paper, we propose an efficient data partitioning and coding algorithm for an error-resilient transmission of DCT coefficients in error prone environment. In the typical data partitioning for Inter-coded frames, motion and macroblock header information is separated from the texture information. It can be an effective tool for the transmission of video over the error prone environment. For Intra-coded frames, however, the loss of DCT coefficients is fatal because there is no other information to reconstruct the corrupted macroblocks by errors. Conventional data partitioning algorithm for DCT coefficients is to separate a fixed number of the significant DCT coefficients from the remaining coefficients, called the spectral separation. While the spectral separation can guarantee an error resilient transmission with small overhead, the main drawback is a significant decrease in the image quality of the high priority partition, compared with that of the bitstreams without data partitioning for an equivalent bit-rate. In the proposed scheme, the quantized DCT coefficients are partitioned into an even-value approximation and the odd remainder part. We also propose a simple and efficient coding algorithm for the odd remainder part. It is shown that the proposed algorithm provides a better image quality than the conventional methods with a little overhead.     

COMPRESSED SPEECH SIGNAL SENSING BASED ON THE STRUCTURED BLOCK SPARSITY WITH PARTIAL KNOWLEDGE OF SUPPORT

Structural and statistical characteristics of signals can improve the performance of Com-pressed Sensing (CS). Two kinds of features of Discrete Cosine Transform (DCT) coefficients of voiced speech signals are discussed in this paper. The first one is the block sparsity of DCT coefficients of voiced speech formulated from two different aspects which are the distribution of the DCT coefficients of voiced speech and the comparison of reconstruction performance between the mixed program and Basis Pursuit (BP). The block sparsity of DCT coefficients of voiced speech means that some algorithms of block-sparse CS can be used to improve the recovery performance of speech signals. It is proved by the simulation results of the mixed program which is an improved version of the mixed program. The second one is the well known large DCT coefficients of voiced speech focus on low frequency. In line with this feature, a special Gaussian and Partial Identity Joint (GPIJ) matrix is constructed as the sensing matrix for voiced speech signals. Simulation results show that the GPIJ matrix outperforms the classical Gaussian matrix for speech signals of male and female adults.     

基于DCT-TCQ的SAR原始数据压缩算法

该文提出了一种基于离散余弦变换(DCT)和网格编码量化(TCQ)的SAR原始数据压缩算法。SAR原始数据可以看成是距离向和方位向的2维线性调频信号的线性平移叠加,因而含有丰富的频率分量,对DCT系数按频率分组,根据各组频率分量系数方差确定量化比特分配,然后对量化系数进行TCQ编码量化,可以大幅度提高了量化增益。真实SAR原始数据实验结果表明:该算法使SAR原始数据的压缩性能指标较现有算法有了明显提高。