Krasner B, Lo S C, Mun S K
Department of Radiology, Georgetown University Hospital, Washington, DC 20007.
J Digit Imaging. 1993 Aug;6(3):164-71. doi: 10.1007/BF03168489.
Pruned-tree structured vectored quantization (PTSVQ) was applied to the lower five gray scale remapped bits of normal and fatty ultrasound liver images. The upper bits were compressed reversibly. This combination of techniques is termed PTSVQ with splitting. The effect of the compression on the difference in texture between normal and fatty liver images was studied at different compression rates and distortions. The changes in texture were measured by changes in the principal components of the covariance matrix of image vectors. The vectors were the same size as those used in the compression technique. There were clear differences in the components of normal and fatty liver images. These differences were largely removed by the PTSVQ with splitting technique even at average single pixel distortions several times smaller than the image noise. These results suggest that the effect of compression on second order statistics should be measured when evaluating algorithms in addition to the first order average distortion.
剪枝树结构矢量量化（PTSVQ）应用于正常和脂肪肝超声图像的低五位灰度重映射位。高位进行可逆压缩。这种技术组合被称为带分割的PTSVQ。在不同压缩率和失真情况下，研究了压缩对正常和脂肪肝图像纹理差异的影响。通过图像向量协方差矩阵主成分的变化来测量纹理变化。这些向量与压缩技术中使用的向量大小相同。正常和脂肪肝图像的成分存在明显差异。即使在平均单像素失真比图像噪声小几倍的情况下，带分割技术的PTSVQ也能基本消除这些差异。这些结果表明，在评估算法时，除了一阶平均失真外，还应测量压缩对二阶统计量的影响。
