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一种改进的自组织特征映射图像压缩算法 总被引:1,自引:0,他引:1
为改善矢量量化的码书性能,提高神经网络的学习效率,在分析Kohonen自组织特征映射算法的基础上,提出一种改进的自组织特征映射算法,并应用到图像的矢量量化中。新算法引入失真敏感参数,并对网络学习参数进行了优化。实验表明,在压缩比为51.2时,新算法恢复图像的峰峰信噪比达到34.66dB,较Kononen自组织特征映射算法提高3.57dB。 相似文献
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提出了适用于子波变换系数的矢量量化方法--子波/分类矢量量化(W/CVQ)。以子波变换系数中对应于图像边缘信息的零交叉片段的具体情况为依据,将子波变换图像矢量分为不同的类别,然后为各类矢量建立码本。初步实验结果表明,该方法能克服传统矢量量化编码子波交换系数不能准确恢复有关边缘信息的缺点,此结果在光学实时指纹识别系统中的应用表明,它能够充分保留原因图像的信息,保证识别系统的准确识别。 相似文献
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量化方法及其统计特征量用于图像检索的性能比较 总被引:3,自引:0,他引:3
分别对标量量化,矢量量化以及分类矢量量化等不同量化方法及其统计特征量用于图像检索的性能进行了分析和比较,对进一步实现支持检索的图像压缩算法具有一定的指导意义。 相似文献
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改进的Kohonen网络及图像自适应矢量量化 总被引:6,自引:2,他引:4
本文针对图像矢量量化存在的分块效应问题,通过对Kohonen自组织模型的研究,修改了Kohonen的自组织特征映射(SOFM)算法,设计了两个DCT(离散余弦变换)域的特征值,用于图像数据块的分类。在此基础上,进一步探讨了改进的自组织特征映射(MSOFM)算法在图像自适应矢量量化中的应用。计算机模拟实验表明,MSOFM算法有效地减少了分块效应,与SOFM算法相比具有更好的性能。 相似文献
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用神经网络实现图像矢量量化是一种非常有效的方法,而小波变换又是近年来迅速发展起来的新算法。文中提出一种改进的误差竞争学习算法,分析了图像在小波变换后数据的特点,提出了新的矢量构造方法,从而最终得到了基于小波变换和误差竞争学习的矢量量化图像压缩新算法(以下简称VQWDCL),无论是在主客观效果上,还是在计算复杂度上,其性能都优于传统的基于小波变换和LBG算法的矢量量化。 相似文献
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图像矢量量化—频率敏感自组织特征映射算法 总被引:17,自引:0,他引:17
用神经网络实现图像矢量量化是一种非常有效的方法,本文在分析自组织特征映射(SOFM)算法的基础上,提出了一种频率敏感自组织特征映射(FSOFM)算法,并对网络学习训练参数的优化进行了探讨。实验表明,FSOFM算法优于SOFM算法。 相似文献
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Neural networks for vector quantization of speech and images 总被引:6,自引:0,他引:6
Krishnamurthy A.K. Ahalt S.C. Melton D.E. Chen P. 《Selected Areas in Communications, IEEE Journal on》1990,8(8):1449-1457
Using neural networks for vector quantization (VQ) is described. The authors show how a collection of neural units can be used efficiently for VQ encoding, with the units performing the bulk of the computation in parallel, and describe two unsupervised neural network learning algorithms for training the vector quantizer. A powerful feature of the new training algorithms is that the VQ codewords are determined in an adaptive manner, compared to the popular LBG training algorithm, which requires that all the training data be processed in a batch mode. The neural network approach allows for the possibility of training the vector quantizer online, thus adapting to the changing statistics of the input data. The authors compare the neural network VQ algorithms to the LBG algorithm for encoding a large database of speech signals and for encoding images 相似文献
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The author considers vector quantization that uses the L (1) distortion measure for its implementation. A gradient-based approach for codebook design that does not require any multiplications or median computation is proposed. Convergence of this method is proved rigorously under very mild conditions. Simulation examples comparing the performance of this technique with the LBG algorithm show that the gradient-based method, in spite of its simplicity, produces codebooks with average distortions that are comparable to the LBG algorithm. The codebook design algorithm is then extended to a distortion measure that has piecewise-linear characteristics. Once again, by appropriate selection of the parameters of the distortion measure, the encoding as well as the codebook design can be implemented with zero multiplications. The author applies the techniques in predictive vector quantization of images and demonstrates the viability of multiplication-free predictive vector quantization of image data. 相似文献
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矢量量化(VQ)是一种极其重要的信号压缩方法,广泛地应用于图像信号压缩、语音信号压缩领域。它I的主要问题是码本设计,在码本设计过程中,有许多算法被提出。本文提出了PSO和LBG算法相结合的1PSO—LBG算法采设计码本,改善了码本质量,提高了收敛速度。 相似文献
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本文提出了基于改进禁止搜索(TS)算法的矢量量化(VQ)码书设计方法.禁止搜索算法的关键是如何定义一个解以及如何在当前解的基础上生成邻域解.由于码书设计的两个优化准则是最邻近条件和聚类质心条件,本文提出了两种禁止搜索算法的解描述方案,其相应算法分别叫基于码书的禁止搜索(CB-TS)算法和基于聚类划分的禁止搜索(PB-TS)算法.为了提高禁止搜索算法的性能,文中在禁止搜索算法中融入了模拟退火(SA)机制.为了进一步提高码书性能,文中还将码书设计的传统LBG算法融入禁止搜索算法中.结果表明,基于禁止搜索的两种码书设计方案所生成的码书性能都比LBG算法有明显提高. 相似文献
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Gimeno Gost D. Torres L. 《Vision, Image and Signal Processing, IEE Proceedings -》1999,146(3):151-158
Vector quantisation (VQ) has been extensively used as an effective image coding technique. One of the most important steps in the whole process is the design of the codebook. The codebook is generally designed using the LBG algorithm which uses a large training set of empirical data that is statistically representative of the images to be encoded. The LBG algorithm, although quite effective for practical applications, is computationally very expensive and the resulting codebook has to be recalculated each time the type of image to be encoded changes. Stochastic vector quantisation (SVQ) provides an alternative way for the generation of the codebook. In SVQ, a model for the image is computed first, and then the codewords are generated according to this model and not according to some specific training sequence. The SVQ approach presents good coding performance for moderate compression ratios and different type of images. On the other hand, in the context of synthetic and natural hybrid coding (SNHC), there is always need for techniques which may provide very high compression and high quality for homogeneous textures. A new stochastic vector quantisation approach using linear prediction which is able to provide very high compression ratios with graceful degradation for homogeneous textures is presented. Owing to the specific construction of the method, there is no block effect in the synthetised image. Results, implementation details, generation of the bit stream and comparisons with the verification model of MPEG-4 are presented which prove the validity of the approach. The technique has been proposed as a still image coding technique in the SNHC standardisation group of MPEG 相似文献
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Ruey-Feng Chang Wen-Tsuen Chen Jia-Shung Wang 《Signal Processing, IEEE Transactions on》1992,40(1):221-225
The Linde-Buzo-Gray (LBG) algorithm is usually used to design a codebook for encoding images in vector quantization. In each iteration of this algorithm, one must search the full codebook in order to assign the training vectors to their corresponding codewords. Therefore, the LBG algorithm needs a large computation effort to obtain a good codebook from the training set. The authors propose a finite-state LBG (FSLBG) algorithm for reducing the computation time. Instead of searching the entire codebook, they search only those codewords that are close to the codeword for a training vector in the previous iteration. In general, the number of these possible codewords can be made very small without sacrificing performance. By only searching a small part of the codebook, the computation time is reduced. In experiments, the performance of the FSLBG algorithm in terms of signal-to-noise ratio is very close to that of the LBG algorithm. However, the computation time of the FSLBG algorithm is about 10% of the time required by the LBG algorithm 相似文献
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图像矢量量化(VQ)是图像压缩算法中的重要环节,在VQ中起决定性因素的是构造出性能优异的码书。为改善矢量量化码书的性能,文中在分析Kohonen自组织特征映射(SOFM)的基础上,提出一种识别距离SOFM的算法,同时将矢量量化应用于图像的小波变换域。测试结果表明,改进的算法使码书设计的计算量得到明显的降低,而且码书的性能得到了提高。 相似文献
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Vector quantization (VQ) is an efficient technique for data compression and has been successfully used in various applications.
The methods most commonly used to generate a codebook are the Linde, Buzo, Gray (LBG) algorithm, fuzzy vector quantization
(FVQ) algorithm, Kekre‘s Fast Codebook Generation (KFCG) algorithm, discrete cosine transform based (DCT-based) codebook generation
method, and k-principle component analysis (K-PCA) algorithm. However, if the separation boundaries in codebook generation
are nonlinear, their performance can degrade fast. In this paper, we present a kernel fuzzy learning (KFL) algorithm, which
takes advantages of the distance kernel trick and the gradient-based fuzzy clustering method, to create a codebook automatically.
Experiments with real data show that the proposed algorithm is more efficient in its performance compared to that of the LBG,
FVQ, KFCG, and DCT-based method, and to the K-PCA algorithm. 相似文献
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矢量量化(VQ)是语音识别中广泛应用的一种数据压缩和编码方法。在矢量量化的码本设计过程中,经典的LBG算法收敛速度快,但极易陷入局部最优,且初始码本的生成对最佳码本的设计影响很大。考虑到遗传算法(GA)是一种具有全局优化搜索能力的算法,提出了GA和LBG算法相结合的GA L算法来优化码本,改善了码本质量,并将其应用于非特定人汉语连续数字语音识别中。实验结果表明,GA L算法优于传统的LBG算法。 相似文献
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A complexity reduction technique for image vector quantization 总被引:2,自引:0,他引:2
A technique for reducing the complexity of spatial-domain image vector quantization (VQ) is proposed. The conventional spatial domain distortion measure is replaced by a transform domain subspace distortion measure. Due to the energy compaction properties of image transforms, the dimensionality of the subspace distortion measure can be reduced drastically without significantly affecting the performance of the new quantizer. A modified LBG algorithm incorporating the new distortion measure is proposed. Unlike conventional transform domain VQ, the codevector dimension is not reduced and a better image quality is guaranteed. The performance and design considerations of a real-time image encoder using the techniques are investigated. Compared with spatial domain a speed up in both codebook design time and search time is obtained for mean residual VQ, and the size of fast RAM is reduced by a factor of four. Degradation of image quality is less than 0.4 dB in PSNR. 相似文献