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Nowadays digital cameras are essential parts of various technological processes and daily tasks. They are widely used in optics and photonics, astronomy, biology and other various fields of science and technology such as control systems and video-surveillance monitoring. One of the main information limitations of photo- and videocameras are noises of photosensor pixels. Camera’s photosensor noise can be divided into random and pattern components. Temporal noise includes random noise component while spatial noise includes pattern noise component. Temporal noise can be divided into signal-dependent shot noise and signal-nondependent dark temporal noise. For measurement of camera noise characteristics, the most widely used methods are standards (for example, EMVA Standard 1288). It allows precise shot and dark temporal noise measurement but difficult in implementation and time-consuming. Earlier we proposed method for measurement of temporal noise of photo- and videocameras. It is based on the automatic segmentation of nonuniform targets (ASNT). Only two frames are sufficient for noise measurement with the modified method. In this paper, we registered frames and estimated shot and dark temporal noises of cameras consistently in the real-time. The modified ASNT method is used. Estimation was performed for the cameras: consumer photocamera Canon EOS 400D (CMOS, 10.1 MP, 12 bit ADC), scientific camera MegaPlus II ES11000 (CCD, 10.7 MP, 12 bit ADC), industrial camera PixeLink PL-B781F (CMOS, 6.6 MP, 10 bit ADC) and video-surveillance camera Watec LCL-902C (CCD, 0.47 MP, external 8 bit ADC). Experimental dependencies of temporal noise on signal value are in good agreement with fitted curves based on a Poisson distribution excluding areas near saturation. Time of registering and processing of frames used for temporal noise estimation was measured. Using standard computer, frames were registered and processed during a fraction of second to several seconds only. Also the accuracy of the obtained temporal noise values was estimated.
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