Iterative Adaptive Photon-Counting Compressive Imaging Based on Wavelet Entropy Automatic Threshold Acquisition

We demonstrate an iterative adaptive photon-counting compressive imaging system. The low-resolution image obtained from the previous sampling are used to calculate the wavelet coefficients. A method based on multiple micro-mirrors combination is proposed to conduct iterative adaptive sampling on the imaging regions corresponding to important children wavelet coefficients at all levels. In order to reconstruct a better quality image directly with appropriate compression ratio and time and avoid speculative selection of thresholds, an automatic threshold acquisition method based on wavelet entropy is proposed, which can automatically follows the change of the object image to obtain the threshold. The iterative adaptive compressive sensing measurement method based on wavelet entropy automatic threshold acquisition is applied to photon-counting compressive imaging system. Experimental results show that a high resolution image can be reconstructed with low compression ratio and short time in extremely low light environment, the quality of reconstructed images of iterative adaptive compressive sensing measurement is better than that of adaptive basis scan.