Abstract: 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.

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。