Abstract a new vector quantization watermarking algorithm was proposed 摘要提出了一种基于蚁群算法优化的矢量量化水印算法。
A classified vector quantization scheme of still image based on wavelet transform 一种基于小波分解的图象分层分类矢量量化方法
One of the emerging technologies for lossy image compression is vector quantization ( vq ) 矢量量化技术由于其极高的压缩效率,正日渐受到研究人员的重视。
vector quantization ( vq ) is a popular lossy compression scheme widely used in multimedia data compressions 矢量量化是一种常用有损压缩技术,被广泛地应用于多媒体数据压缩。
During the training phase, codebooks based on extracted features are generated via vector quantization approach 在训练阶段,每一个说话者通过矢量量化产生一个码书(语音数据库)。
The swarm intelligence algorithm and the theory of vector quantization ( vq ) data compression are summarized systemically in the paper 本文较系统地综述了群体智能算法和矢量量化数据压缩理论。
Finite-state vector quantization; lpc cepstral coefficients; dynamic spectral feature; dynamic time warpping; state transition function 有限状态矢量量化lpc倒谱系数动态谱特性动态规整状态转移函数
In this dissertation, a image compression coding method based on wavelet transformation and vector quantization is discussed in detail 本文详细研究了基于小波变换和矢量量化的静态图像压缩编码方法。
And then, we apply multiwavelet filter banks in image compression, using two method ( new vector quantization algorithm and improvement ezw ) 然后,对应于单小波零树算法,提出一种新方法,将多小波应用于零树压缩。
At first, the error model of the vector quantization, watermarking embedding and the noisy channel were established and further the simplified model was given 为了用蚁群算法进行优化,首先建立了矢量量化、水印嵌入及通过噪声通道的误差模型,并给出了简化模型。