Reduction of discrete cosine transform/ quantisation/inverse quantisation/inverse discrete cosine transform computational complexity in H.264 video encoding by using an efficient prediction algorithm

This study develops a novel prediction algorithm to effectively save the computational complexity of discrete cosine transform (DCT), quantisation (Q), inverse Q (IQ), and inverse DCT (IDCT) in video encoding for H.264 applications. Based on the DC value of the DCT coefficients that is equal to the sum of residual data in the 4times4 sub-macroblock (sub-MB), a mathematical model is built to develop a prediction algorithm for reducing the computations in the DCT/Q/IQ/IDCT process. Experimental results and comparisons demonstrate that the proposed prediction algorithm significantly reduces the encoding time while incurring little additional overhead, and lowers the bit rate with little peak signal-to-noise ratio degradation.     

适用于分布式视频编码框架的整数离散余弦变换算法

鉴于H.264的整数离散余弦变换(DCT)算法及其量化方法复杂度高,难以直接应用于分布式视频编码(DVC)框架的现状,提出了一种基于大跨度定长(步长为2的正整数次方)量化的整数DCT算法及变换基生成方法。该算法充分地利用整数DCT基的可伸缩特性寻找最迎合硬件工作原理的变换基,在保证“小”变换基的同时将编码器的伸缩量化阶段“转移”到解码器一端以降低编码器复杂度。在“转移”过程中,该算法利用DCT系数饱和放大保证图像质量,利用DCT系数的溢出上限保证算法的可靠性,通过减小基偏差提高压缩性能。实验结果表明,与H.264对应模块相比,该算法的量化方式便于位平面提取,在图像质量达到准无损压缩的前提下将编码器的伸缩量化阶段的运算量缩减至16次整型常量加法运算,图像质量与压缩率的性价比提升了23.9%,适用于分布式编码框架。     

A comparison of fast inverse discrete cosine transform algorithms

The discrete cosine transform (DCT) is often applied to image compression to decorrelate picture data before quantization. This decorrelation results in many of the quantized transform coefficients equaling zero, hence the compression gain. At the decoder, very few nonzero quantized transform coefficients are received, so the input to the inverse DCT is sparse, greatly reducing the required computation. This paper describes different styles of implementations of fast inverse DCTs designed especially for sparse data and compares them on workstation processors.This research has been sponsored by ARPA     

Wavelet domain-based video noise reduction using temporal discrete cosine transform and hierarchically adapted thresholding

A novel spatio-temporal filter for video denoising, which operates entirely in the wavelet domain, is proposed. For effective noise reduction, the spatial and temporal redundancies that exist in the wavelet domain representation of a video signal are exploited. First, a 2D discrete wavelet transform is applied to the input noisy frames. This is followed by a discrete cosine transform (DCT), which is applied to the temporal subband coefficients to minimise the redundancy among the consecutive frames. The DCT transformed, noise-free coefficients in the different wavelet domain subbands for the original image sequence are modelled using a prior having a generalised Gaussian distribution. On the basis of this prior, filtering of the noisy wavelet coefficients in each subband is carried out using a new, low-complexity wavelet shrinkage method, which utilises the correlation that exists between subsequent resolution levels. Experimental results show that the proposed scheme outperforms several state-of-the-art spatio-temporal filters in terms of both the peak signal-to-noise ratio and the visual quality     

A motion compensated lifting wavelet codec for 3D video coding

A motion compensated lifting (MCLIFT) ramework for the 3D wavelet video coding is proposed in this paper,By using bi-directional motion compensation in each lifting step of the temporal direction,the video frames are effectively de-correlated,With the proper entropy coding and bit-stream packaging schemes,the MCLIFT wavelet video coder is scalable at frame rate and quality level .Experimental results show that the MCLIFT video coder outperforms the 3D wavelet video coder without motion by an average of 0.9-1.3dB,and outperforms MPEG-4 coder by an average of 0.2-0.6dB.     

An improved 3D wavelet-based scalable video coding codec for MC-EZBC

With the rapid growth of modern multimedia applications, 3D wavelet-based scalable video coding (SVC) codec has received considerable attention lately because of its high coding performance and flexibility in bitstream scalability. It combines the motion-compensated temporal filtering (MCTF) together with the spatial decomposition to produce an embedded bitstream offering various levels of video quality over the heterogeneous networks. However, in the existing 3D wavelet-based SVC schemes, where the block types for block matching algorithms are limited, weighting matrices for block-wise motion compensation are fixed, and variations in activities of temporal subbands are not considered in the selection of the Lagrange multiplier for mode decision. In this paper, our major contribution is to provide some recent extensions to the well-known scalable subband/wavelet video codec Motion-Compensated Embedded Zero Block Coding (MC-EZBC) using three novel and content adaptive algorithms. Firstly, the enhanced hierarchical variable size block matching (Enhanced HVSBM) algorithm is proposed for the variable block size motion estimation. Then, the rate-distortion optimization (RDO) based adaptive Lagrange multiplier selection model for mode decision is presented. Finally, we introduce the adaptive weighting matrices design for overlapped block motion compensation (OBMC). Experimental results show that all the three proposed algorithms significantly improve the overall coding performance of MC-EZBC. Comparisons with other popular wavelet-based SVC codecs demonstrate the effectiveness of our improved codec in terms of both video quality assessment and computational complexity.     

基于余弦变换和小波变换的数字水印算法

在互联网络技术和多媒体技术普及的今天,数字水印技术已经成为目前信息安全技术领域的一个重要方向。本文提出了一种基于离散余弦变换和离散小波变换的数字水印算法,以一个长度为n服从N(0,1)正态分布的随机数序列作为水印信号嵌入到图像最具感知意义的频率部分。实验结果表明,此算法具有良好的视觉效果和鲁棒性。     

基于离散小波变换和离散余弦变换域的扩频水印盲提取算法

针对扩频水印的盲提取问题,提出了一种在数字音频中扩频水印的盲提取算法。算法将扩频后的水印信息隐藏在音频文件小波分解的低频系数再做离散余弦变换(DCT)后的第5个系数中。提取时在扩频序列及其长度均未知的情况下,采用二次谱和奇异值分解(SVD)的方法对嵌入时使用的扩频参数进行估计,实现了数字音频中扩频水印的盲提取。仿真实验表明,所提算法在未知扩频参数的情况下能提取出归一化系数(NC)为1的水印图像并且水印的鲁棒性也很强,在加噪、低通滤波等攻击下估计出的扩频序列正确率能达到90%以上,恢复出的水印图像清晰可见,归一化系数都在0.98以上。     

Fast 2D discrete cosine transform on compressed image in restricted quadtree and shading format

Given a compressed image in the restricted quadtree and shading format, this paper presents a fast algorithm for computing 2D discrete cosine transform (DCT) on the compressed grey image directly without the need to decompress the compressed image. The proposed new DCT algorithm takes O(K²logK+N²) time where the decompressed image is of size N×N and K denotes the number of nodes in the restricted quadtree. Since commonly K<N, the proposed algorithm is faster than the indirect method by decompressing the compressed image first, then applying the conventional DCT algorithm on the decompressed image. The indirect method takes O(N²logN) time.     

二维翻转结构9/7离散小波逆变换研究与VLSI实现

采用提升结构的二维9/7离散小波逆变换模块是高清图像解码显示和实时处理的关键支撑技术。为实现电路模块的整体优化,在提升结构二维9/7离散小波逆变换标准算法的研究基础上,通过分析图像数据的输入输出顺序,结合器件模型提出一种翻转结构的优化算法。进一步地,给出了所提算法的一种多核并行VLSI结构：通过流水线技术将关键路径降为一级乘法器延迟;通过重组织数据流,处理N×N大小的图像仅需4N的中间缓存,从而在提升该模块速率的同时降低了中间缓存。基于Sparten6-xc6slx150t FPGA进行综合验证,结果表明该模块可稳定运行于166.34 MHz时钟速率。     

Real-time motion estimation for image and video processing applications

This contribution focuses on different topics that are covered by the special issue titled “Real-Time Motion Estimation for image and video processing applications” and which incorporate GPUS, FPGAs, VLSI systems, DSPs, and Multicores, among other platforms. The guest editors have solicited original contributions, which address a wide range of theoretical and practical issues related to high-performance motion estimation image processing including, but not limited to: real-time matching motion estimation systems, real-time energy-based motion estimation systems, gradient-based motion estimation systems, optical flow estimation systems, color motion estimation systems, multi-scale motion estimation systems, optical flow and motion estimation systems, analysis or comparison of specialized architectures for motion estimation systems and real-world applications.     

基于DFRCT滤波器组自适应语音增强算法

提出一种改进的语音增强方法,将带噪语音信号进行子带分解,再对子带信号进行离散分数余弦变换（DFRCT）域滤波,利用了DFRCT良好的正交特性,且自适应滤波采用最小均方（LMS）算法。对滤波后的信号进行DFRCT逆变换得到增强后的子带语音信号,合成增强后的语音信号。仿真结果表明,该算法在减少输入信号自相关程度的基础上,提高了收敛速度,减少了计算时间（约10 s）,增强后的语音信号的分段信噪比（SegSNR）和PESQ值都有所提高,具有良好的语音增强效果。     

A semi-fragile watermarking scheme for authenticating audio signal based on dual-tree complex wavelet transform and discrete cosine transform

In this paper, a novel semi-fragile watermarking scheme for authenticating an audio signal based on dual-tree complex wavelet transform (DT-CWT) and discrete cosine transform (DCT) is proposed. Specifically, the watermark data are efficiently inserted into the coefficients of the low-frequency sub-band of DT-CWT taking advantages of both DCT and quantization index modulation (QIM). First, the original digital audio signal is segmented and then performed with DT-CWT. Second, based on the energy compression property, the low-frequency sub-band coefficients of the DT-CWT domain are performed with DCT, and the DC component is utilized to embed one distorted watermark bit by the QIM technique. Finally, inverse DCT and DT-CWT are orderly implemented on the watermarked coefficients of each audio segment to get a watermarked audio signal. Simulation results show that the hybrid embedding domain constructed by DT-CWT and DCT is effective, and the proposed watermarking scheme is not only inaudible, but also robust against content persistent non-malicious audio signal processing operations, such as MP3 compression, noise addition, re-sampling, re-quantization, etc. Furthermore, the proposed scheme can effectively authenticate the veracity and integrity of audio content and greatly expands the applicability of the audio watermarking scheme.     

A lossy 3D wavelet transform for high-quality compression of medical video

In this paper, we present a lossy compression scheme based on the application of the 3D fast wavelet transform to code medical video. This type of video has special features, such as its representation in gray scale, its very few interframe variations, and the quality requirements of the reconstructed images. These characteristics as well as the social impact of the desired applications demand a design and implementation of coding schemes especially oriented to exploit them. We analyze different parameters of the codification process, such as the utilization of different wavelets functions, the number of steps the wavelet function is applied to, the way the thresholds are chosen, and the selected methods in the quantization and entropy encoder. In order to enhance our original encoder, we propose several improvements in the entropy encoder: 3D-conscious run-length, hexadecimal coding and the application of arithmetic coding instead of Huffman. Our coder achieves a good trade-off between compression ratio and quality of the reconstructed video. We have also compared our scheme with MPEG-2 and EZW, obtaining better compression ratios up to 119% and 46%, respectively for the same PSNR.     

An algebraic method for synthesizing fast algorithms of discrete cosine transform of arbitrary size

An algebraic method for synthesizing fast algorithms of the discrete cosine transform (DCT) of arbitrary size is proposed. The method is based on the polynomial algebra $\mathbb{F}{{[x]} \mathord{\left/ {\vphantom {{[x]} {p(x)}}} \right. \kern-0em} {p(x)}}$ associated with the DCT. The fast DCT algorithm comes as a result of the step-by-step decomposition of this algebra. In turn, the decomposition requires step-by-step factorization of the polynomial p(x). This problem is solved using Galois??s theory, which allows finding all the subfields of the splitting field of the polynomial p(x) where p(x) can be factorized.     

基于DCT域的高压缩图像去块效应算法

块离散余弦变换(B lock D iscrete Cosine Transform)的主要缺点是在低比特率时其恢复图像的块边界上会出现明显可见的方块效应,降低了图像的视觉质量.为了尽量消除块效应并保护图像的边缘信息提出了一种基于DCT域的块效应消除算法.该算法充分利用了人类视觉系统(Hum an V isual System)特性,建立了块效应模型并给出一个简便的检测边缘标准,对于平滑区,对影响块效应的参数进行修正,然后用线性函数块代替阶跃函数块去除块效应,最后再对更新块和纹理区在DCT域中进行后滤波.仿真结果验证了本文算法的有效性.     

Real-time 3D shape reconstruction, dynamic 3D mesh deformation, and high fidelity visualization for 3D video

3D video [IEEE Multimedia (1997) 18] is the ultimate image media recording dynamic visual events in the real world as is; it records time varying 3D object shape with high fidelity surface properties (i.e., color and texture). Its applications cover wide varieties of personal and social human activities: entertainment (e.g., 3D game and 3D TV), education (e.g., 3D animal picture books), sports (e.g., sport performance analysis), medicine (e.g., 3D surgery monitoring), culture (e.g., 3D archive of traditional dances), and so on. In this paper, we propose: (1) a PC cluster system for real-time reconstruction of dynamic 3D object action from multi-view video images, (2) a deformable 3D mesh model for reconstructing the accurate dynamic 3D object shape, and (3) an algorithm of rendering natural-looking texture on the 3D object surface from the multi-view video images. Experimental results with quantitative performance evaluations demonstrate the effectiveness of these methods in generating high fidelity 3D video from multi-view video images.     

Recursive algorithm, architectures and FPGA implementation of the two-dimensional discrete cosine transform

A new recursive algorithm and two types of circuit architectures are presented for the computation of the two-dimensional discrete cosine transform (2D DCT). The new algorithm permits to compute the 2D DCT by a simple procedure of the 1D recursive calculations involving only cosine coefficients. The recursive kernel for the proposed algorithm contains a small number of operations. Also, it requires a smaller number of pre-computed data compared with many of existing algorithms in the same category. The kernel can be easily implemented in a simple circuit block with a short critical delay path. In order to evaluate the performance improvement resulting from the new algorithm, an architecture for the 2D DCT designed by direct mapping from the computation structure of the proposed algorithm has been implemented in an FPGA board. The results show that the reduction of the hardware consumption can easily reach 25% and the clock frequency can increase 17% compared with a system implementing a recently reported 2D DCT recursive algorithm. For a further reduction of the hardware, another architecture has been proposed for the same 2D DCT computation. Using one recursive computation block to perform different functions, this architecture needs only approximately one-half of the hardware that is required in the first architecture, which has been confirmed by an FPGA implementation.     

An integrated index for identification of fatty liver disease using radon transform and discrete cosine transform features in ultrasound images

Alcoholic and non-alcoholic fatty liver disease is one of the leading causes of chronic liver diseases and mortality in Western countries and Asia. Ultrasound image assessment is most commonly and widely used to identify the Non-Alcoholic Fatty Liver Disease (NAFLD). It is one of the faster and safer non-invasive methods of NAFLD diagnosis available in imaging modalities. The diagnosis of NAFLD using biopsies is expensive, invasive, and causes anxiety to the patients. The advent of advanced image processing and data mining techniques have helped to develop faster, efficient, objective, and accurate decision support system for fatty liver disease using ultrasound images. This paper proposes a novel feature extraction models based on Radon Transform (RT) and Discrete Cosine Transform (DCT). First, Radon Transform (RT) is performed on the ultrasound images for every 1 degree to capture the low frequency details. Then 2D-DCT is applied on the Radon transformed image to obtain the frequency features (DCT coefficients). Further the 2D-DCT frequency coefficients (features) obtained are converted to 1D coefficients vector in zigzag fashion. This 1D array of DCT coefficients are subjected to Locality Sensitive Discriminant Analysis (LSDA) to reduce the number of features. Then these features are ranked using minimum Redundancy and Maximum Relevance (mRMR) ranking method. Finally, highly ranked minimum numbers of features are fused using Decision Tree (DT), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Support Vector Machine (SVM), Fuzzy Sugeno (FS) and AdaBoost classifiers to get the highest classification performance. In this work, we have obtained an average accuracy, sensitivity and specificity of 100% in the detection of NAFLD using FS classifier. Also, we have devised an integrated index named as Fatty Liver Disease Index (FLDI) by fusing two significant LSDA components to distinguish normal and FLD class with single number.