基于曲率尺度空间的VOP形状编码算法

首先对曲率尺度空间（CSS）算法进行改进，并用改进的CSS算法对任意形状物体的形状信息进行特征点的分层提取；其次，用自适应算术编码算法对固定长度的八分圆编码算法进行改进，并对所提取的特征点进行算术编码，实验结果表明，这种新的基于特征点提取的形状编码方法比MPEG-4校验模型中基于上下文的算术形状编码算法，在Dn相同的条件下，主观质量更好，且压缩比更高。     

无损大容量数据嵌入算法

提出了一种新的无损的数据嵌入算法,可应用于军事、法律、医学等需要无损图像的领域.使用了改进的LSB作为嵌入算法并对原图的未修改部分进行了预测、上下文模型与量化、算术编码.预测减少了空间冗余,上下文模型进一步利用了空间相关性和位平面相关.基于上下文模型的算术编码获得了更好的压缩效率和压缩容量.实验证明嵌入数据后的图像损伤小并可完全恢复.     

基于上下文快速有效的自适应二进制算术编码实现

介绍算术编码的原理和基于模型的自适应算术编码算法,并利用二进制高效率的索引树这样一个数据结构对传统的自适应算术编码进行了改进。实验表明,无论对于高度集中的数据集还是对于分布较为均匀的数据集,在运行时间上新算法都有较大的改进。验证了该算法在提高解的精度和加快收敛速度方面都有显著改善,从而为解决函数优化问题提供了一种行之有效的新方法.     

一个基于算术编码的灰度图象无损压缩算法

本文介绍了一个基于算术编码的灰度图象无损压缩算法，它以JPEGT－LS算法为基础，采用了一系列有利于算术编码的改进措施，获得了满意的压缩效果。     

改进的算术编码

算术编码是基于统计的、无损数据压缩效率最高的方法。对于算术编码的进位问题，目前广泛使用的是Ｒｉｓｓａｎｅｎ和Ｌａｎｇｄｏｎ提出的比特填充技术。本文提出进位陷阱技术，不必人为插入填充比特就可以解决进位问题，因而能够得到一个确切的数，并使解码端得到很好的简化。以进位陷阱的思想为基础，本文提出算术编码和一种简捷的终止技术，称为中值终止技术，并重新构造了算术编码和解码算法。本文讨论了算术编码和分析性质，得     

算术编码在图像信号压缩中的应用

阐述了算术编码的有限精度描述及其推导过程。并对几种不同的算术编码模型进行了测试分析，提出了一种采用算术编码对特定格式的图形文件进行压缩的算法，并论证了该算法实现的优势。     

基于自适应子带分解和内容模型的图像编码

在SPIHT算法基础上引入了两种算法——自适应子带分解算法和基于内容模型的算术编码算法，以改进压缩性能．自适应子带分解算法改变了小波变换后系数的统计分布，在低码率时峰值信噪比(PSNR)得到一定的改善；基于内容模型的算术编码算法进一步开发了子带间以及相邻像素间的相关性，增强了压缩性能．实验结果表明：文中算法和STIHT算法比较，改进了压缩性能，同时保留了零树算法的渐进传输等优点。     

一种基于上下文的自适应算术编码技术在无损图像压缩中的应用

本文提出了一种改进的基于上下文的自适应算术编码算法,为了在算术编码中选择合适的上下文,该算法法使用加权最小均方误差法来预测当前变换系数的值,并给出评测本算法性能的实验结果。     

基于单队列递归扫描的嵌入式零树图象编码方法

为了提高基于互联网的图象编码的压缩比和多带宽适应性，提出了一种新的嵌入式零树图象编码方法，该方法首先在连续累进量化方法中使用单队列算法，从而不仅无需使用动态队列，而且率失真特性也得到改善；其次设计了一种基于空间树递归扫描的零树编码快速算法，因而完全解决了重复扫描问题；最后基于编码符号的频带内邻域相关性，为自适应算术编码定义一种新的Markov模型，实验结果表明，该算法在保持高粒度多码率特性的同时，压缩效率较EZW算法有明显提高。     

位平面算术编码的编码分离与MQ编码器改进

为了降低图像压缩中位平面算术编码的计算复杂度,提出了将算术编码从位平面扫描中分离,方便编码的并行计算。以JPEG2000的位平面编码为例,实现了位平面扫描和MQ编码的分离,然后根据编码分离后的算法特点,设计了一种改进的MQ编码器。对该算法在TMS320C6000系列DSP中的实现进行了研究,通过软件流水、循环展开、条件操作和优化选项等方法提高处理速度。编码独立和编码器改进相结合,使重建图像质量稍有提高,编码速度提高了8倍以上。     

Multimedia Selective Encryption by Means of Randomized Arithmetic Coding

We propose a novel multimedia security framework based on a modification of the arithmetic coder, which is used by most international image and video coding standards as entropy coding stage. In particular, we introduce a randomized arithmetic coding paradigm, which achieves encryption by inserting some randomization in the arithmetic coding procedure; notably, and unlike previous works on encryption by arithmetic coding, this is done at no expense in terms of coding efficiency. The proposed technique can be applied to any multimedia coder employing arithmetic coding; in this paper we describe an implementation tailored to the JPEG 2000 standard. The proposed approach turns out to be robust towards attempts to estimating the image or discovering the key, and allows very flexible protection procedures at the code-block level, allowing to perform total and selective encryption, as well as conditional access.     

通用的高性能算术编码器

文中基于成熟的ＱＭ算术编码器,提出了对称二叉树的编码方式ＳＴＱＭ和最优二叉树的编码方式ＯＴＱＭ。ＳＴＱＭ与ＯＴＱＭ均是大符号集熵编码器。它们不仅保持了ＱＭ编码器的超过９６％的编码效率,也保持了它高速运算的特性。基中ＯＴＱＭ可以动态的调整码树结构,使得编码速度达到理论最优值。ＳＴＱＭ由于可并行性和逻辑线路设计简单等特点,使之适合于做动态旬图像的基于专用硬件设计的熵编码模块。     

自适应算术编码及其在JPEG2000中的应用

自适应算术编码是一种高效的熵编码方法。本文较为详细地介绍了自适应算术编码的工作原理和实现方法,以及在JPEG2000的应用情况,分析了自适应算术编码应用于图像压缩编码的实现过程,并讨论了实现过程中应该解决的若干技术问题。     

Adaptive Signal Modeling Based on Sparse Approximations for Scalable Parametric Audio Coding

This paper deals with the application of adaptive signal models for parametric audio coding. A fully parametric audio coder, which decomposes the audio signal into sinusoids, transients and noise, is here proposed. Adaptive signal models for sinusoidal, transient, and noise modeling are therefore included in the parametric scheme in order to achieve high-quality and low bit-rate audio coding. In this paper, a new sinusoidal modeling method based on a perceptual distortion measure is proposed. For transient modeling, a fast and effective method based on matching pursuit with a mixed dictionary is chosen. The residue of the previous models is analyzed as a noise-like signal. The proposed parametric audio coder allows high quality audio coding for one-channel audio signals at 16 kbits/s (average bit rate). A bit-rate scalable version of the parametric audio coder is also proposed in this work. Bit-rate scalability is intended for audio streaming applications, which are highly demanded nowadays. The performance of the proposed parametric audio coders (nonscalable and scalable coders) is assessed in comparison to widely used audio coders operating at similar bit rates.      

基于CAC的数字视频安全编码研究

对于视频压缩领域,基于上下文的自适应编码(CAC)是一类新出现的高效熵编码方法。为了对数字视频进行实时安全编码,提出了一种基于CAC的数字视频安全编码方案,并首先建立了以CAC安全编码器为核心的安全编码链,然后给出了基于上下文的自适应二进制算术安全编码(CABASC)和基于上下文的自适应变长安全编码(CAVLSC)两种安全编码操作。实验结果表明,该方案具有较好的安全性、实时性和软件易实现性,可作为进一步研究CAC安全编码的基础。     

Gaussian Mixture Kalman Predictive Coding of Line Spectral Frequencies

Gaussian mixture model (GMM)-based predictive coding of line spectral frequencies (LSFs) has gained wide acceptance. In such coders, each mixture of a GMM can be interpreted as defining a linear predictive transform coder. In this paper, we use Kalman filtering principles to model each of these linear predictive transform coders to present GMM Kalman predictive coding. In particular, we show how suitable modeling of quantization noise leads to an adaptive a posteriori GMM that defines a signal-adaptive predictive coder that provides improved coding of LSFs in comparison with the baseline recursive GMM predictive coder. Moreover, we show how running the GMM Kalman predictive coders to convergence can be used to design a stationary GMM Kalman predictive coding system which again provides improved coding of LSFs but now with only a modest increase in run-time complexity over the baseline. In packet loss conditions, this stationary GMM Kalman predictive coder provides much better performance than the recursive GMM predictive coder, and in fact has comparable mean performance to a memoryless GMM coder. Finally, we illustrate how one can utilize Kalman filtering principles to design a postfilter which enhances decoded vectors from a recursive GMM predictive coder without any modifications to the encoding process.     

基于FPGA的AVS-P2熵编码器设计

本文重点研究了AVS—P2熵编码器的算法、结构以及利用FPGA实现的若干关键问题，给出了详细的块变换系数熵编码器硬件结构，并通过了仿真验证。实现中提出了一种新的2D—VLC码表存储结构和一种确定指数哥伦布码码长的方法，可以节省59％的码表存储空间和降低指数哥伦布码码长计算电路的硬件复杂度。     

视频编码中算术编码的二进制化研究

二进制化是自适应二进制算术编码中的重要步骤,在二进制级别进行概率估计与编码,能有效降低编解码计算复杂度。本文提出一种新型二进制化方法,根据相邻变换块的非零系数个数存在的高度相关性,对变换块的非零系数个数进行自适应二进制化;在设计二进制化算法的过程中,还针对概率分布近似对称的情况,提出一种简化的将语法元素映射为码字序号的规则。实验结果表明,与传统方法相比,新的算法能在压缩效率相当的前提下,有效降低计算复杂度。     

Context-based embedded image compression using binary wavelet transform

Binary wavelet transform (BWT) has several distinct advantages over the real wavelet transform (RWT), such as the conservation of alphabet size of wavelet coefficients, no quantization introduced during the transform and the simple Boolean operations involved. Thus, less coding passes are engaged and no sign bits are required in the compression of transformed coefficients. However, the use of BWT for the embedded grayscale image compression is not well established. This paper proposes a novel Context-based Binary Wavelet Transform Coding approach (CBWTC) that combines the BWT with a high-order context-based arithmetic coding scheme to embedded compression of grayscale images. In our CBWTC algorithm, BWT is applied to decorrelate the linear correlations among image coefficients without expansion of the alphabet size of symbols. In order to match up with the CBWTC algorithm, we employ the gray code representation (GCR) to remove the statistical dependencies among bi-level bitplane images and develop a combined arithmetic coding scheme. In the proposed combined arithmetic coding scheme, three highpass BWT coefficients at the same location are combined to form an octave symbol and then encoded with a ternary arithmetic coder. In this way, the compression performance of our CBWTC algorithm is improved in that it not only alleviate the degradation of predictability caused by the BWT, but also eliminate the correlation of BWT coefficients in the same level subbands. The conditional context of the CBWTC is properly modeled by exploiting the characteristics of the BWT as well as taking advantages of non-causal adaptive context modeling. Experimental results show that the average coding performance of the CBWTC is superior to that of the state-of-the-art grayscale image coders, and always outperforms the JBIG2 algorithm and other BWT-based binary coding technique for a set of test images with different characteristics and resolutions.     

Optimal Coding of Quantized Laplacian Sources for Predictive Image Compression

This paper discusses the optimal coding of uniformly quantized Laplacian sources. The techniques known for designing optimal codes for sources with infinite alphabets are used for the quantized Laplacian sources which have probability mass functions with two geometrically decaying tails. Due to the simple parametric model of the source distribution the Huffman iterations are possible to be carried on analytically, using the concept of reduced source, and the final codes are obtained as a sequence of very simple arithmetic operations, avoiding the need to store coding tables. Comparing three uniform quantizers, we find one which consistently outperforms the others in the rate-distortion sense. We foresee for the newly introduced codes an important area of applications in low complexity lossy image coding, since similar codes, designed for two-sided geometrical sources, became the basic tools used in JPEG-LS lossless image compression.