Abstract
The sensitivity of incoherent optical methods using video cameras (e.g., optical flow and digital image correlation) for full-field displacement measurements, defined by the minimum measurable displacements, is essentially limited by the finite bit depth of the digital camera due to the quantization with round-off error. Quantitatively, the theoretical sensitivity limit is determined by the bit depth B as δp = 1/(2B − 1) [pixel] which corresponds to a displacement causing an intensity change of one gray level. Fortunately, the random noise in the imaging system may be leveraged to perform a natural dithering to overcome the quantization, rendering the possibility of breaking the sensitivity limit. In this work we study such a theoretical sensitivity limit and present a spatiotemporal pixel-averaging method with dithering to achieve super-sensitivity. The numerical simulation results indicate that super-sensitivity can be achieved and is quantitatively determined by the total pixel number N for averaging and the noise level σn as $\delta p^{*} \propto (\sigma _{n}/\sqrt {N})\delta p$.
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Data/code underlying the theoretical simulation results presented in this paper are available in Code 1 [10].
10. S. Li, “Theoretical simulation of super-sensitivity optical flow by pixel-averaging with dithering,” figshare(2022),https://doi.org/10.6084/m9.figshare.20811886.v1
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