Image compression with adaptive Haar-Walsh tilings
Image compression with adaptive Haar-Walsh tilings
复制标题
使用自适应 Haar-Walsh 平铺进行图像压缩
DOI：
10.1117/12.408575
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
L. Villemoes
中科院分区：
文献类型：
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作者：
M. Lindberg;L. Villemoes
我们执行自适应联合空间和频率平铺，包括所有级别的Haar-Walsh小波包树的二维信号。该方法在非线性逼近方面给出了令人惊讶的良好结果。用这种方法压缩后的图像的视觉质量与使用Haar滤波器时使用两倍小波系数和标准小波包的质量相同。当允许所有水平时，描述获胜系数的位置的成本是不可忽略的。该方法引入了一个平铺信息向量来描述所选基，利用该信息可以方便、快速地重建原始图像。对于图像压缩，该倾斜信息向量被压缩到仅对应于保持系数的那些节点，并且这使得自适应方案具有竞争力。
We perform adaptive joint space and frequency tilings including all levels in the Haar-Walsh wavelet packet tree for 2D signals. The method gives surprisingly good results in terms of nonlinear approximation. The visual quality of the compressed images with this method is the same as the quality using twice the number of coefficients for wavelets and standard wavelet packets when Haar filters are used. When all levels are allowed the cost for description of the location of the winning coefficients is not negligible. A tiling information vector is introduced for description of the chosen basis and the original image can be easily and quickly reconstructed using this information. For image compression, this tilting information vector is compressed to only those nodes which correspond to kept coefficients, and this makes the adaptive scheme competitive.