一种新颖的基于哈德码变换的码字搜索算法

针对图像矢量量化编码的复杂性,提出了一种新颖的快速最近邻码字搜索算法。该算法首先计算出每个码字和输入矢量的哈德码变换,然后为输入矢量选取范数距离最近的初始匹配码字,利用多控制点的三角不等式和两条有效的码字排除准则,把不匹配的码字排除,最后选取与输入矢量最匹配的码字。实验结果表明,新算法相比于其他算法,在保证编码质量的前提下,码字搜索时间和计算量均有了明显降低。     

一种改进的AEI算法中初始匹配码字的快速查找方法

矢量量化（VQ）是一种高效的有损压缩技术。快速码字搜索算法是矢量量化的核心问题之一,其性能决定了编码时间。快速码字搜索算法中,绝对误差不等式删除算法(AEI)是一种典型的3步算法,其第1步查找输入矢量的初始匹配码字的方法采用了Minimax法,是整个AEI算法中计算量最大的步骤,严重影响了算法的效率。针对这个问题,提出了一种新的查找初始匹配码字的方法——Partial Minimax法。该方法在保证所找到的初始匹配码字与原始AEI算法相同并且重建图像的PSNR（峰值信噪比）值不变的前提下,可显著减小这一步骤的计算量和查找时间,从而有效地提高了算法的总体编码速度。     

基于哈夫曼编码的矢量量化图像压缩算法

现有边缘匹配矢量量化(SMVQ)算法没有考虑码字索引分布规律。针对该问题,通过理论分析得到码字索引严重非均匀分布的规律,基于该规律提出结合哈夫曼编码的SMVQ图像压缩算法。实验结果表明,与穷尽搜索算法相比,该算法在保持相同编码质量的情况下,编码码率下降50%,与SMVQ相比,其PSNR提高0.8 dB,编码码率下降30%。     

一种快速相关预测矢量量化的图像编码算法

矢量量化是近年来图像压缩研究中的重要技术，在该技术中，减小编码运算时间和降低平均编码比特率是当前研究的重要问题，目前，已经提出了许多快速编码算法。为了进一步减少图像矢量量化编码的时间和降低编码比特率，提出了一种超前相关预测与快速搜索相结合的快速矢量量化编码算法。该算法在对当前图像块完成编码后，再根据该图像块与相邻的未编码图像块的相关性来预测相邻块的编码值，如果预测成功，则用低比特率表示编码值；否则用绝对误差不等式删除(AEI)算法来求得高比特率编码值，以减少总编码时间和降低平均比特率。测试结果表明，该算法比传统的穷尽搜索算法的编码速度快，且比特率低，同时对编码质量的影响很小。     

均值与矢量量化复合快速图像编码算法

矢量量化是一种有效的数据压缩技术,由于其算法简单,具有较高的压缩率,因而被广泛应用于数据压缩编码领域。通过对图像块灰度特征的研究,根据图像的平滑与否,提出了对图像进行均值和矢量量化复合编码算法,该算法对平滑图像块采用均值编码,对非平滑块采用矢量量化编码。这不仅节省了平滑码字的存储空间,提高了码书存储效率,并且编码速度大大提高。同时采用码字旋转反色（2R）压缩算法将码书的存储容量减少到1/8,并结合最近邻块扩展搜索算法（EBNNS）对搜索算法进行优化。在保证图像画质的前提下,整个系统的图像编码速度比全搜索的普通矢量量化平均提高约7.7倍。     

基于改进的参考矢量选取的码字快速搜索算法

矢量量化的编码过程计算复杂性极高,为了减少编码时大量的矢量间距离计算,许多文献提出利用不等式关系以较少的计算量来估算距离的方法。在Chang等人提出的利用双限制三角不等式的快速搜索算法基础上,通过改进参考矢量的选取方法,有效提高了码字搜索的效率。实验结果表明,改进算法的码字排除率可以提高3.735%9.976%,编码时间可以减少6.03%35.25%。     

自适应子矢量划分的快速码字搜索算法

矢量量化编码过程中需要进行大量的矢量间距离计算,这个过程的计算复杂度极高,严重限制了其实际使用。为了加速矢量量化的编码过程,已经提出了各种基于1维特征量的码字搜索算法来减小码字搜索的范围。本文在基于不等式的快速搜索算法基础上,通过使用更有效的基于特征量的搜索算法,并引入自适应子矢量划分的方法,将额外增加的存储空间从N(N-1)/2降低到了13N,码字搜索范围减小了33.88%～50.94%,编码时间减少了10.82%～27.16%。     

一种基于动态码书的矢量量化图像编码算法

针对快速相关矢量量化算法重建图像质量不高、存在明显方块效应的问题，采用后向搜索一定区域的预测与有限状态矢量量化相结合的编码方法，并用MEENS-2和PDS结合搜索算法完成码字搜索。实验结果表明，该编码方法既提供了高压缩比，又减少了额外失真的影响，保证了图像的重建质量。     

基于DCT分类的边缘匹配矢量量化图像编码算法

提出一种基于DCT分类的边缘匹配矢量量化算法,充分考虑了当前处理图像块与其相邻图像块之间的相关性以及各码字与该输入矢量之间的边缘匹配失真.实验结果表明,该算法的峰值信噪比(PSNR)值高于基本边缘匹配矢量量化器且码率更低.本文对该方法进行了改进,提出一种新的基于DCT分类的边缘匹配矢量量化算法.该算法可以使运算时间缩短40%～5O%.     

基于快速相关矢量量化的图象编码算法

图象编码已经成为当今计算机世界的重要问题,而矢量量化（ＶＱ）又是近年来有损图象压缩的一种重要技术,它的优点是比特率低以及解码简单,但是其穷尽搜索编码计算量较大,为了降低编码时间,已经有多种快速算法出现在一些文献中,然而这些算法往往不能进一步降低比特率,为了解决这一问题,因此提出了一种新颖快速相关矢量量化（ＣＶＱ）图象编码算法,该算法对图象块的编码采用对角顺序,即在编码过程中根据当前图象块（ＣＶＱ）     

Hadamard transform based fast codeword search algorithm for high-dimensional VQ encoding

An efficient nearest neighbor codeword search algorithm for vector quantization based on the Hadamard transform is presented in this paper. Four elimination criteria are derived from two important inequalities based on three characteristic values in the Hadamard transform domain. Before the encoding process, the Hadamard transform is performed on all the codewords in the codebook and then the transformed codewords are sorted in the ascending order of their first elements. During the encoding process, firstly the Hadamard transform is applied to the input vector and its characteristic values are calculated; secondly, the codeword search is initialized with the codeword whose Hadamard-transformed first element is nearest to that of the input vector; and finally the closest codeword is found by an up-and-down search procedure using the four elimination criteria. Experimental results demonstrate that the proposed algorithm is much more efficient than the most existing nearest neighbor codeword search algorithms in the case of problems of high dimensionality.     

H.264/SVC mode decision based on mode correlation and desired mode list

Design of video encoders involves implementation of fast mode decision (FMD) algorithm to reduce computation complexity while maintaining the performance of the coding. Although H.264/scalable video coding (SVC) achieves high scalability and coding efficiency, it also has high complexity in implementing its exhaustive computation. In this paper, a novel algorithm is proposed to reduce the redundant candidate modes by making use of the correlation among layers. A desired mode list is created based on the probability to be the best mode for each block in base layer and a candidate mode selection in the enhancement layer by the correlations of modes among reference frame and current frame. Our algorithm is implemented in joint scalable video model (JSVM) 9.19.15 reference software and the performance is evaluated based on the average encoding time, peak signal to noise ration (PSNR) and bit rate. The experimental results show 41.89% improvement in encoding time with minimal loss of 0.02 dB in PSNR and 0.05% increase in bit rate.     

分级视频编码中宏块相关性快速模式决策

为降低空时分级视频编码中自适应层间预测模式的计算复杂度,利用增强层中时域宏块相关性的特点,提出一种随时间等级变化的快速模式决策算法。该算法将参考宏块使用过的模式按照其率失真优化代价排序,选择其中代价较小的模式作为当前宏块的动态备选方案,从而有效地提高编码效率。在JSVM上的实验结果表明,同原有非优化决策算法相比,在PSNR平均降低0.0148dB、比特率增加0.55%的情况下,该优化算法使得平均编码时间减少21.67%。     

矢量量化中码书旋转压缩的研究

普通码书中的码字之间在不同的方向上具有很大的相关性,存在大量的数据冗余。提出了将码书中的码字旋转压缩的理论。该理论是将各个码字按四个方向垂直旋转后进行相似性检查。如果旋转后的码字其中一个方向上与前面的码字存在相似,则将该码字删除,从而达到压缩的目的。编码时将压缩后的码书旋转恢复后进行编码,从而大幅降低了需要存储的码字数量。同时给出了一种将现有1 024阶16维码书旋转压缩成256阶16维的方法,并对该方法得到的码书性能进行了仿真验证。实验结果表明使用压缩后的码书在硬件实现时与普通的矢量量化码书相比减少了75%的存储空间和输入带宽,而PSNR平均只降低0.28 dB。     

基于统计的SVC层间编码快速模式决策算法

可分级视频编码提供了较为灵活的编码方式,但层间模式决策算法增加了编码器的计算复杂度。该文分析了基本层和增强层间模式分布的相关性,设计一种层间编码快速模式决策算法。实验结果表明,在PSNR平均仅降低0.04 dB、码率减少0.096%的前提下,该优化算法能使编码时间平均减少50.34%。     

A fast VQ codebook generation algorithm using codeword displacement

In this paper, we present a fast codebook generation algorithm called CGAUCD (Codebook Generation Algorithm Using Codeword Displacement) by making use of the codeword displacement between successive partition processes. By implementing a fast search algorithm named MFAUPI (Modified Fast Algorithm Using Projection and Inequality) for VQ encoding in the partition step of CGAUCD, the codebook generation time can be further reduced significantly. Using MFAUPI, the computing time of CGAUCD can be reduced by a factor of 4.7–7.6. Compared to Generalized Lloyd Algorithm (GLA), our proposed method can reduce the codebook generation time by a factor of 35.9–121.2. Compared to the best codebook generation algorithm to our knowledge, our approach can further reduce the corresponding computing time by 26.0–32.8%. It is noted that our proposed algorithm can generate the same codebook as that produced by the GLA. The superiority of our method is more remarkable when a larger codebook is generated.     

Adaptive rate control for motion JPEG2000

Rate and quality-constrained rate control is very effective for video applications, since it can maintain constant quality while eliminating local rate spikes. An adaptive rate control method based on image activity measures (ARCIAM) is proposed for Motion JPEG2000. The algorithm can efficiently adjust the compressed bit rates to meet the rate and quality constraints for different types of colour sequences. It predicts the ratedistortion (RD) slope thresholds for frames based on image activity measure (IAM) before entropy coding. Thus, the encoding of unnecessary coding passes can be avoided. Experimental results show that the proposed method can meet the quality and rate constraints, and can achieve quality performance comparable to post-compression rate distortion optimisation at the same bit rate. Under 3 bpp and 40 dB constraints, ARCIAM can reduce the total encoding time and tier-1 encoding time for sequences by more than 20 and 30%, respectively. Moreover, the memory requirement for buffering bit-streams and RD-slope information is reduced by more than 30% on average. Besides, the method can be incorporated into the line-based JPEG2000 encoding system easily, and has been implemented on Kakadu.