多进制小波在医学图像检索中的应用

医学影像的数据量日益增加使得建立一个高效的医学检索系统势在必行，而提高检索系统效率的关键技术就是合理地分类图像。纹理作为图像灰度的分布模式，是图像的重要特征之一。由于图像的小渡多尺度分解本质上是一种多通道的滤波过程，其多分辨率分析结构与人类视觉系统特性相一致。因而，在图像的多进制小坡变换域中提取不同分辨率下的纹理特征，特别有利于图像识别与检索。文中设计并实现了一种基于八进制小波的医学图像分类方法，更好地解决了医学图像检索的关键技术，得到了很高的分类率。

Application of multi-band wavelets to medical image retrieval

Along with the increasing medical image data, it is imperative to set up an effective system about medical image retrieval. Essentially, the image classification is crucial for medical image retrieval. As a distribution pattern of image gray scale, texture is an important character. Wavelet multi-scale decomposition is essentially multi-channel filtering and its multi-resolution analysis structure is identical with human visual system. So the extraction of texture feature under different resolutions after multi-band wavelets transform is of great benefit to image recognition and image retrieval. Consequently, this paper designs an image classification method based on eight-band wavelet. This method solves the key technology in the medical image retrieval, and it gains very high classification rate.