共查询到20条相似文献,搜索用时 0 毫秒
1.
《Real》1996,2(4):241-247
Vector quantization is a popular data compression technique due to its theoretical advantage over scalar quantization which enables exploitation of the dependencies between neighboring samples. However, the complexity of the encoding process imposes certain limitations on the size of the codebook population and/or the dimensions of the processed blocks. In this paper, we show that this complexity can be conveniently distributed as subcodebooks over general purpose MIMD parallel processors, to provide almost linearly scalable throughput and flexible configurability. A particular advantage of this approach is that it makes feasible the use of higher dimensional image blocks and/or larger codebooks, leading to improved coding performance with no penalty in execution speed compared with the original sequential implementation. As an example, we show that an implementation with 12 transputers using 8 × 8 blocks and 4096 codebook entries reduces the bit-rate by a factor of 2.625 and runs faster than a sequential implementation based upon 4 / 4 blocks and 256 codebook entries, while producing a similar PSNR. 相似文献
2.
一种压缩比自适应的快速矢量量化算法 总被引:1,自引:1,他引:1
提出了一种压缩比自适应的矢量量化(VQ)编解码算法,将图像预先分为16×16的分块,根据图像块的平滑程度,减少重复搜索的运算量,大幅提高压缩比和编码速度,而解码图像的峰值信噪比(PSNR)只有很少下降。对于10幅标准图像的测试结果表明,与普通VQ相比,该文算法的压缩比平均提高54%,PSNR平均仅降低0.86%。对于单纯背景的图像,压缩比可达到200∶1左右。算法简单,适合硬件实现。 相似文献
3.
针对传统学习矢量量化算法没有考虑属性的重要度差异的问题,提出一种加权学习矢量量化算法.该算法为每一维属性引入一个权重系数,用其表征相应属性在分类过程中的重要程度,并与权向量一同更新.利用输入样本和获胜神经元之间的修正距离的均值,控制权重系数更新的阈值及步长.距离均值确保了更新过程的稳定性,且无需进行权重系数的归一化操作.UCI机器学习数据库中6组数据的实验结果表明,该算法能够有效给出数据的本质属性,尤其是局部型权重系数.与传统学习矢量量化算法及其改进算法相比,识别率高、性能稳定、计算复杂度低. 相似文献
4.
图象盲复原所面临的主要问题是可利用信息的不足,所以必须充分利用图象本身及成像系统的先验信息,为此,结合模糊先验辨识的思想,给出了一种新的空间自适应正则化算法,该算法先用交替最小化的迭代方法对模糊进行先验辨识,然后利用辨识结果,用各向异性扩散进行图象复原,算法充分利用了图象及成像系统(或点扩散函数PSF)的分段平滑特性,同时又利用各向异性扩散的概念,使得正则化不仅在程度上,而且在方向上都是空间自适应的,从而能够有效地进行图象盲复原,仿真结果表明,该算法的复原效果优于空间自适应各向同性正则化(SAR)算法,其收敛性能优于空间自适应各向异性正则化(SAAR)算法。 相似文献
5.
This paper presents a novel self-creating neural network scheme which employs two resource counters to record network learning activity. The proposed scheme not only achieves the biologically plausible learning property, but it also harmonizes equi-error and equi-probable criteria. The training process is smooth and incremental: it not only avoids the stability-and-plasticity dilemma, but also overcomes the dead-node problem and the deficiency of local minimum. Comparison studies on learning vector quantization involving stationary and non-stationary, structured and non-structured inputs demonstrate that the proposed scheme outperforms other competitive networks in terms of quantization error, learning speed, and codeword search efficiency. 相似文献
6.
在互联网和无线通信环境下,图像通信常因数据包传输出错或丢生而导致质量的严重下降,多描述编码是解决这个问题的一种新途径。该文提出了一种多描述网格编码矢量量化新算法,给出了多描述分解的方法和规则,并通过构造一个代价函数,提出了最优搜索策略,用维特比算法对多描述编码最优路径进行搜索。仿真结果表明,新算法有效利用网格编码矢量量化将量化码书大小扩大一倍的特性,提高了中央通道的编码性能,而如果只收到单个描述,解码图像仍能获得较好的重建质量。 相似文献
7.
矢量量化的遗传k-均值算法 总被引:2,自引:0,他引:2
提出了一种遗传k-均值算法,该算法通过改进标准遗传操作及采用可变变异率,使其在矢量量化应用中表现出很好的性能.实验证明,该算法能够获得质量高于k-均值和模糊k-均值算法的矢量量化码书,为设计全局最优码书提供了新思路。 相似文献
8.
分析了模糊矢量量化(FVQ)图象编码的原理,给出了FVQ设计三要素。提出了用于图象编码的指数型模糊矢量量化算法(FVQE)。实验结果表明,FVQE的图象编码性能与FVQ相当,但收敛速度要略快于FVQ算法。 相似文献
9.
Agiomyrgiannakis Y. Stylianou Y. 《IEEE transactions on audio, speech, and language processing》2007,15(2):377-386
In many speech-coding-related problems, there is available information and lost information that must be recovered. When there is significant correlation between the available and the lost information source, coding with side information (CSI) can be used to benefit from the mutual information between the two sources. In this paper, we consider CSI as a special VQ problem which will be referred to as conditional vector quantization (CVQ). A fast two-step divide-and-conquer solution is proposed. CVQ is then used in two applications: the recovery of highband (4-8 kHz) spectral envelopes for speech spectrum expansion and the recovery of lost narrowband spectral envelopes for voice over IP. Comparisons with alternative approaches like estimation and simple VQ-based schemes show that CVQ provides significant distortion reductions at very low bit rates. Subjective evaluations indicate that CVQ provides noticeable perceptual improvements over the alternative approaches 相似文献
10.
一种新的矢量量化编码算法 总被引:1,自引:0,他引:1
矢量量化是低位率图像压缩非常有效的一种方法 ,矢量量化基本方法的一个关键问题是需要较长的编码时间 ,尤其对于高维矢量或大的码书 .提出了一种基于 1/ 2 L2 -范数金字塔数据结构的快速编码算法 ,明显加快了编码过程 ,减少了实际对存储器的需求 ,特别对高维矢量和大的码书效果更显著 ,同时保持与全搜索方法相同的编码质量 相似文献
11.
We introduce a batch learning algorithm to design the set of prototypes of 1 nearest-neighbour classifiers. Like Kohonen's LVQ algorithms, this procedure tends to perform vector quantization over a probability density function that has zero points at Bayes borders. Although it differs significantly from their online counterparts since: (1) its statistical goal is clearer and better defined; and (2) it converges superlinearly due to its use of the very fast Newton's optimization method. Experiments results using artificial data confirm faster training time and better classification performance than Kohonen's LVQ algorithms. 相似文献
12.
13.
《Digital Signal Processing》1999,9(2):89-106
We address the problem of speech compression at very low rates, with the short-term spectrum compressed to less than 20 bits per frame. Current techniques apply structured vector quantization (VQ) to the short-term synthesis filter coefficients to achieve rates of the order of 24 to 26 bits per frame. In this paper we show that temporal correlations in the VQ index stream can be introduced by dynamic codebook ordering, and that these correlations can be exploited by lossless coding approaches to reduce the number of bits per frame of the VQ scheme. The use of lossless coding ensures that no additional distortion is introduced, unlike other interframe techniques. We then detail two constructive algorithms which are able to exploit this redundancy. The first method is a delayed-decision approach, which dynamically adapts the VQ codebook to allow for efficient entropy coding of the index stream. The second is based on a vector subcodebook approach and does not incur any additional delay. Experimental results are presented for both methods to validate the approach. 相似文献
14.
在经典的空间几何线性均值收缩算法的基础上,提出了一种非线性空间几何收缩算法。由实验表明,该算法不仅能提高压缩比,而且对信噪比也有一定的改善。 相似文献
15.
文章提出了一种最大概率匹配的矢量量化编码算法,它为码书中的每一码字增加一个计数器,统计在编码图象时每个码字的出现的频数,并进行排序;在量化矢量时,根据当前码字出现频数大小依次选择侯选码字,即频数大的码字优先选为候选码字。该算法可以和已有的预测法结合,形成预测加最大概率匹配的联合矢量量化编码算法。实验表明,联合算法的效率较高,在最初几次的搜索中就能以较高的命中率命中最佳匹配码字。 相似文献
16.
改进的分形矢量量化编码 总被引:1,自引:0,他引:1
为了提高图象的分形矢量量化编码效果,在利用四叉树对图象进行自适应分割的基础上,基于正交基三维分量投影准则,提出了图象块非平面近似方法,进而形成一种新的静态图象分形矢量量化编码方法。该方法首先通过对投影参数进行DPCM编码来构造粗糙图象,然后由此来构成差值图象编码的码书。由于该方法把分形和矢量量化编码结合起来,因此解码时只需查找码书,并仅进行对比度变换。计算机编、解码实验结果表明,该编码方法具有码书不需外部训练,解码也不需迭代等优点,且与其他同类编码器相比,该方法在压缩比和恢复图象质量(PSRN)方面均有明显改善。 相似文献
17.
Muñoz-Perez J. Gomez-Ruiz J. A. Lopez-Rubio E. Garcia-Bernal M. A. 《Neural Processing Letters》2002,15(3):261-273
In this paper, we develop a necessary and sufficient condition for a local minimum to be a global minimum to the vector quantization problem and present a competitive learning algorithm based on this condition which has two learning terms; the first term regulates the force of attraction between the synaptic weight vectors and the input patterns in order to reach a local minimum while the second term regulates the repulsion between the synaptic weight vectors and the input's gravity center to favor convergence to the global minimum This algorithm leads to optimal or near optimal solutions and it allows the network to escape from local minima during training. Experimental results in image compression demonstrate that it outperforms the simple competitive learning algorithm, giving better codebooks. 相似文献
18.
19.
20.
空间矢量数据存贮方式与索引机制的发展 总被引:7,自引:0,他引:7
空间矢量数据的存贮方式与索引机制直接影响到地理信息系统的整体性能,对它们发展的了解有助于地理信息系统的使用与开发。介绍了空间矢量数据的存贮方式和索引机制的演变过程,并总结了各自的特点。 相似文献