基于平稳小波的工业计算机断层图像压缩

Haina Jiang, Xiangyu Yang, Li Zeng
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引用次数: 1

摘要

为了获得更高的分辨率和精度,工业计算机断层成像的数据量越来越大。此外,工业计算机断层扫描图像是近似分段常数,适合编码轮廓。然后,我们提出了一种改进的基于小波轮廓编码的压缩方法。首先,我们将Freeman编码思想融合到我们的IMCE(一种改进的基于平稳小波的轮廓提取方法)中来提取轮廓。同时,IMCE提取的每一个等高线点,利用其连续性和逻辑联系,通过记录相对坐标而不是实际坐标的方式直接存储。将传统的基于轮廓的压缩方法的两个步骤简化为一个步骤。最后,采用霍夫曼编码对其进行进一步无损压缩。实验结果表明,该方法在获得较好的压缩比的同时,仍能保持较理想的图像质量。
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Compressing industrial computed tomography images based on stationary wavelet
To have higher resolution and precision, the amount of industrial computed tomography data has become larger and larger. Moreover, industrial computed tomography images are approximately piece-wise constant, which fits for encoding contour. Then, we develop an improved compression method based on wavelet contour coding Firstly, we merge Freeman encoding idea into our IMCE (an improved method for contours extraction based on stationary wavelet) to extract contours. Simultaneously, each contour point extracted by IMCE is directly stored by recording the relative coordinates not the actual ones through exploiting their continuity and logical linking. By that, the two steps of traditional contour-based compression method are simplified into only one. Lastly, Huffman coding is employed to further lossless compress them. Experimental results show that this method can gain good compression ratio as well as keeping ideal quality of decompressed image.
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