摘要
提出一种基于DPCM与Hilbert曲线的医疗图像无损压缩方法,通过差分脉码调制技术(DPCM)对图像进行预测处理,得到差值图像,再利用Hilbert曲线对医疗图像像素的进行扫描,得到图像的一维数据,然后分别用哈夫曼编码、游程编码和字典编码对一维数据进行压缩。实验结果显示Hilbert扫描可以增加像素的相关性,对提高压缩比有一定的贡献。
Hilbert scanning can visit neighboring points consecutively without crossing itself in tow-dimensional space.For testing the effect of Hilbert scanning to images compression,the pixels in grey-scale images have been rearranged using Hilbert scanning,then implement four lossless encoding schemes,Huffman coding,run-length encoding,lZW coding and LZ77 coding,along with Hilbert scanning order.The experiments show that Hilbert scanning can enhance pixel locality,and increase the compression ratio effectively.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第6期98-99,共2页
Computer Engineering and Applications
基金
广西自然科学基金(the Nature Science Foundation of Guangxi of Chinaunder Grant No.0640034)。
