Traditional vision-based vibration measurement is fundamentally constrained by the low sampling rates of area-scan cameras and the noise sensitivity of existing motion magnification algorithms. To overcome these spatiotemporal barriers, we propose a high-fidelity framework that integrates ultra-high-speed line-scan imaging with a 1D Complex Morlet Wavelet Phase-Based Video Magnification (CMW-PVM) algorithm. By extracting and manipulating the localized phase of 1D spatial signals, CMW-PVM effectively decouples structural dynamics from background noise while eliminating the computational redundancy associated with 2D spatial pyramid methods. Simulations demonstrate that CMW-PVM significantly extends the linear magnification range (up to α≈35) while preserving exceptional structural fidelity (FSIM >0.87) under severe noise conditions (SNR = 10 dB). Experimental validation against a laser Doppler vibrometer (LDV) reveals near-perfect kinematic accuracy, with a relative amplitude error of only 1.65%. Furthermore, at a 100 Hz high-frequency excitation, the system successfully resolves microscopic displacements (≈10 μm) without temporal aliasing—enabled not by violating sampling theory but by leveraging the high physical line rate of the line-scan sensor. This establishes a robust, non-contact, and computationally efficient paradigm for broadband, micro-amplitude vibration monitoring in industrial environments.
Zhu et al. (Fri,) studied this question.