Non-invasive imaging based on sparse representation

In this paper, we propose a method based on sparse representation to accelerate the scanning technique to perform non-invasive imaging through scattering layers. The scanning time is proportional to the size of the collected integrated intensity pattern and it usually takes tens of hours to finish the collecting process. To speed up the scanning technique, only a much smaller integrated intensity pattern is collected. A training set of integrated intensity pattern pairs with sizes corresponding to the necessary integrated intensity pattern that makes the scanning technique work well and the much smaller one is constructed. And a pair of dictionaries is trained from the constructed set exploiting the K-SVD algorithm. Based on sparse representation, the necessary integrated intensity pattern can be recovered from the much smaller one using the trained dictionaries, thus realizing non-invasive imaging successfully. Experimental results show that our method can successfully make the scanning time reduced by 8/9 without deteriorating the imaging quality of the scanning technique.