Biblio

Compressive sensing is a new technique by which sparse signals are sampled and recovered from a few measurements. To address the disadvantages of traditional space image compressing methods, a complete new compressing scheme under the compressive sensing framework was developed in this paper. Firstly, in the coding stage, a simple binary measurement matrix was constructed to obtain signal measurements. Secondly, the input image was divided into small blocks. The image blocks then would be used as training sets to get a dictionary basis for sparse representation with learning algorithm. At last, sparse reconstruction algorithm was used to recover the original input image. Experimental results show that both the compressing rate and image recovering quality of the proposed method are high. Besides, as the computation cost is very low in the sampling stage, it is suitable for on-board applications in astronomy.

We propose an optical security method for object authentication using photon-counting encryption implemented with phase encoded QR codes. By combining the full phase double-random-phase encryption with photon-counting imaging method and applying an iterative Huffman coding technique, we are able to encrypt and compress an image containing primary information about the object. This data can then be stored inside of an optically phase encoded QR code for robust read out, decryption, and authentication. The optically encoded QR code is verified by examining the speckle signature of the optical masks using statistical analysis. Optical experimental results are presented to demonstrate the performance of the system. In addition, experiments with a commercial Smartphone to read the optically encoded QR code are presented. To the best of our knowledge, this is the first report on integrating photon-counting security with optically phase encoded QR codes.