利用时间拉伸显微成像系统观察并记录非重复动态随机现象，在其超高成像速度和高空间分辨率下必定会产生大量的数据。一种基于差分检测和游程编码的数据压缩方法，可以有效地解决时间拉伸成像系统的数据存储问题。差分检测可以消除连续相同的信号，只检测出相邻信号的差异，从而提高游程编码算法的有效性。实验中，采用扫描频率为77.76 MHz的时间拉伸显微成像对分辨率板、人红细胞和人乳腺癌细胞线性扫描成像。实验结果表明，数据压缩比可以达到8.47，对比分析发现经过差分检测方法可以获得更高的压缩比。另外，通过计算重建后的图像与原图的结构相似性(SSIM)值发现，经过数据压缩后高质量的图像可以被重建。

Serial time-stretch imaging technique with its high line-scan rate can observe and record fast non-repetitive events. However, it is inevitable that a fast imaging system would generate a massive amount of data. This paper proposes a data compression methodbased on differential detection and run-length encoding for time-stretch imaging technique, which can efficiently solve the existing problem of data volume in the back-end digital signal processing. Differential detection can eliminate identical signals and only distinguish the difference between consecutive scans, while the run-length encoding algorithm is suitable for encoding the same repeated signals, to further improve the effectiveness of run-length encoding algorithm. In the experiment, a 77.76 MHz line-scan imaging system is demonstrated with the resolution test target, red blood cell and MCF cell. It turns out that the compression rate of 8.47 is proved. Through analysis, it is found that the method with differential detection can achieve higher compression rate than the method without differential detection, especially when the sampling resolution is low. The structured similarity index measurement(SSIM) calculation between the original image and the reconstructed image shows high quality images can be reconstructed after compression by the proposed method.