一种基于小波变换的医学图像量化编码算法的研究

An Algorithm of A Wavelet-Based Medical Image Quantization

医学图像压缩是远程医疗和 PACS系统中的重要研究课题。研究了小波子带图像系数的统计分布 ,发现小波子带图像系数分布和拉普拉斯分布非常相似 ,继而提出了一种基于其统计特征的图像量化编码算法。该算法以小波子带图像样本标准差为选择量化编码阈值的重要依据。实验表明 ,该算法具有计算简单、不同阈值范围待编码系数可预测以及易于获得较高压缩效率的优点 ,在远程医疗和

The compression of medical image is the key to study tele-medicine & PACS. We have studied the statistical distribution of wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is very much similar to that of Laplacian distribution.Based on the statistical properties of image wavelet decomposition, an image quantization algorithm is proposed. In this algorithm, we selected the sample-standard-deviation as the key quantization threshold in every wavelet subimage. The test has proved that, the main advantages of this algorithm are simple computing and the predictability of coefficients in different quantization threshold range. Also, high compression efficiency can be obtained. Therefore, this algorithm can be potentially used in tele-medicine and PACS.