一种基于小波变换与分类矢量量化的图像压缩算法

为了提高数字图像的压缩比率,提出了一种将小波变换与分类矢量量化相结合的图像压缩算法.该算法首先对图像进行小波分解,充分利用不同尺度小波系数的相关性,并对不同尺度的子图使用分类矢量,不同类使用不同大小的子码书.为了解决高维矢量在算法实现时效率较低的问题,采用非线性插值对构造好的码矢量进行降维.实验表明,该方法在提高图像压缩比的同时,降低了算法的时间复杂度,从而提高了算法的效率.

An Algorithm of Image Compression Based on Wavelet Transform and Classified Vector Quantization

In order to improve the compression ratio of digital image,an new image compression algorithm was proposed. In the algorithm,wavelet transform was combined with vector quantization. Firstly,the relativity of different scales of the wavelet coefficients was used to decompose the wavelet. Then,the classified vector quantization was used in the different scale of the wavelet subbands and different sizes of subcode book were used in different classes. In order to improve the efficiency in high dimensions,the non-linear interpolated vector quantization( NLIVQ) was used to reduce the number of dimensions of the code vector. Experimental results showed that the compression ratio of the image and the efficiency of the algorithm were improved in this new algorithm. In the meantime,the time complexity of the algorithm was discussed.