For a large amount of near-infrared information is introduced to EMCCD, which leads to color distortion in the green plant area during R, G, B channel image fusion. In this paper, an algorithm combing dark channel prior and sub-region correction is proposed. First, the results of dark channel prior and sub-region extraction of green plant areas are analyzed and compared, we find that both of them have shortcomings. Second, on the basis of the preliminary dark channel extraction, binaryzation parameters are determined by analyzing the brightness mean values of various scenes in R, G, B and gray channel, so as to realize the extraction of green plant areas. Finally, the color correction is carried out in different regions and the image is converted from RGB color space to HIS color space. To make full use of the infrared information in the system, the I channel is replaced by gray channel. It is proved that the correction algorithm proposed in this paper can effectively correct the color biased image acquired by EMCCD system.
In the field of low illumination image sensor, the noise of the latest scientific-grade CMOS image sensor is close to EMCCD, and the industry thinks it has the potential to compete and even replace EMCCD. Therefore we selected several typical sCMOS and EMCCD image sensors and cameras to compare their performance parameters. The results show that the signal-to-noise ratio of sCMOS is close to EMCCD, and the other parameters are superior. But signal-to-noise ratio is very important for low illumination imaging, and the actual imaging results of sCMOS is not ideal. EMCCD is still the first choice in the high-performance application field.
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