Super-resolution reconstruction for low-light imaging using intensified CMOS camera: SNR analysis and algorithm improvement

It is difficult for traditional CMOS camera to obtain clear images under extremely low-light conditions for example the new moon or the quarter moon because the photons generated are so few that the signal-to-noise ratio (SNR) is much lower than what is necessary to resolve finer details. Being different from traditional CMOS camera, intensified CMOS, named as ICMOS camera can greatly amplify the very limited arriving photons through external photoelectric effect and thus the corresponding SNR could be improved a lot for low-light conditions. In previous studies, by fusing a series of low-light images having sub-pixel displacement between each other through classical iterative back projection (IBP) reconstruction algorithm, not only the resolution is enhanced but also the SNR increases as well. However why the SNR can be improved through super-resolution reconstruction is not theoretically answered yet. Therefore in this manuscript two contributions are made. In the first place, the characteristics of sub-pixel super-resolution low-light imaging are firstly further investigated. By introducing the concept of spectral SNR, the analytical expression of the SNR before and after super-resolution reconstruction is established, based on which it is concluded that the MTF boosting generated by super-resolution reconstruction is one important factor that can bring in the SNR increment besides inherent noise reducing characteristic of the super-resolution reconstruction algorithm itself. In the second place, by combing the IBP based super-resolution reconstruction algorithm, the FFT (Fast Fourier Transform) based single image amplification and image enhancement methods together, better reconstruction results could be obtained.