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… Click to show full 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 δ p ∗∝(σ n /N)δ p.
               
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