KEYWORDS: Image analysis, Signal to noise ratio, Image processing, Imaging systems, Computer simulations, Digital image processing, Information theory, Image compression, Digital micromirror devices, Sensors
In this paper, an evaluation criterion based on image complexity is proposed in ghost imaging. According to the iterative performance of ghost imaging, characteristic factors of describing image complexity are introduced for seeking a new evaluation criterion to improve evaluation method. The proposed image complexity can be utilized to assess the iterative performance of different ghost imaging algorithms. The assessment results indicate that the proposed image complexity has a similar function with SNR, which is used to evaluate the iterative performance of ghost imaging. Compared with other existing evaluation methods, the obvious advantage is availability when the original image is unknown, and experiment results demonstrate that the new evaluation criterion is valid in ghost imaging.
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