应用CS理论实现同步采样压缩成像

Imaging system of synchronous sample and compression based on CS theory

为了减轻图像数据存储负担,实现图像在网络上的快速传输和实时处理,对一种新的压缩传感(CS)理论进行了研究。介绍了压缩传感理论的主要思想和基于压缩传感理论的光学成像系统,给出了一种新型图像重建算法—和谐正交匹配追踪算法,并进行了相应的模拟实验。实验结果显示,该成像机制可同步完成图像的采样与数据压缩,同时可获得良好的图像重建效果。由于该方法所要传输的信号数据量较小,所以十分有利于远距离的图像传输。

With the aim to realise the transmission of the time processsing and to reduce the amount of data of the digital image information with a high-speed and realstorage, a new theory for image compression, Compressed Sensing（CS） , is investigated to solve the problem. The concept of CS theory is introduced and a system for the optical image based on the CS theory is designed, and then it presents a new algorithm for rebuilding the image--Harmonic Orthogonal Matching Pursuit （HXOMP） algorithm. The corresponding numerical simulation and expremental results show that the imaging mechanism can capture the image and compress the data at the same time, and this method can also obtain good results of rebuilding images. Due to small amount of the data used, this method is very useful to transform images with a long distance.