Multiresolution analysis is an effective approach in signal processing, especially in image processing, to decompose signals in different resolutions.
多分辨率分析是信号处理特别是图像处理的一种新的有效方法，可以在不同尺度上给出信号的信息。
The multiresolution image representation based on the wavelet analysis is introduced. By this way, the image resolution can be decreased in keeping with the human visual system characteristic.
本文基于小波分析提出由高分辨率图像可得到各种较低分辨率图像的多分辨方法符合人的视觉系统特性。
The wavelet transform theory is one of the effective tools mat widely apply to image processing recently, which have charicrictics of multiresolution analysis, fast working time, etc.
小波分析理论是近年来广泛使用于图像处理领域的有效工具之一，具有时域和频域的双重局部性、多尺度分析、计算的快速性等特点。
The hierarchical multiresolution wavelet analysis in conjunction with the contextual information of the image extracted from GMRF results in local features of the image.
在图像的多分辨率小波分析的基础上 ，采用高斯 -马尔可夫随机场模型来描述图像的局部特征 。
The hierarchical multiresolution wavelet analysis in conjunction with the contextual information of the image extracted from GMRF results in local features of the image.
在图像的多分辨率小波分析的基础上 ，采用高斯 -马尔可夫随机场模型来描述图像的局部特征 。
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