In this paper, a multi focus image fusion algorithm is proposed which takes features of human vision system (HVS) into account.
本文提出了一种考虑人眼视觉系统特性的多聚焦图像融合算法。
The wavelet has the good multi-resolution decomposition features, which both have a significant compression of image data, but also retain most of the information of an image.
而小波变换多分辨率分解的优良特性，既能大幅度的压缩图像数据，又能很好的保留图像的绝大部分的信息。
First, this paper st udies those visual features which have be en usually implemented in image correspondence including multi-scale features.
首先，本文研究了在图像配准中常用的一些视觉特征，其中包括多尺度的特征。
Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps.
首先在画素级上提取影像的纹理和形状结构特征，在构建的多尺度分割集影像上提取物件的区域光谱特征。
The features extract method of MCSF based on wavelet multi-scale transform is that the image feature of coefficient sub-frequency is decomposed with 3 layer of wavelet multi-scale transform.
基于小波多尺度分解子带主成份的特征提取法，利用小波多尺度分解子带系数图像特征。
Edge detction based on wavelet multi-scale identity is made. The statistics features based on regional gray and the co-occurrence matrix of gray level are taken as performing image segmentation.
该系统先对粮虫图像进行小波边缘提取，根据灰度共生矩阵和局部统计方法提取小波分割后的图像纹理特征。
Edge detction based on wavelet multi-scale identity is made. The statistics features based on regional gray and the co-occurrence matrix of gray level are taken as performing image segmentation.
该系统先对粮虫图像进行小波边缘提取，根据灰度共生矩阵和局部统计方法提取小波分割后的图像纹理特征。
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