Abstract:This paper reports an efficient method for sound extraction from high-speed light spot videos reconstructed from the coded light spot images captured with a low-speed camera based on compressive sensing, but at the expense of consuming time. The proposed method first gets the high-speed video of the light spot that is illuminated on the vibrating target caused by sound. Then the centroid of the light spot is used to recover the sound. Simulations of the proposed method are carried out and experimental results … Show more
In the optical system for reconstructing speech signals based on laser speckle images, the resonance between the sound source and nearby objects leads to frequency response problem, which seriously affects the accuracy of reconstructed speech. In this paper, we propose a speech enhancement algorithm to reduce the frequency response. The results show that after using the speech enhancement algorithm, the frequency spectrum correlation coefficient between the reconstructed sinusoidal signal and the original sinusoidal signal is improved by up to 82.45%, and the real speech signal is improved by up to 56.40%. This proves that the speech enhancement algorithm is a valuable tool for solving the frequency response problem and improving the accuracy of reconstructed speech.
In the optical system for reconstructing speech signals based on laser speckle images, the resonance between the sound source and nearby objects leads to frequency response problem, which seriously affects the accuracy of reconstructed speech. In this paper, we propose a speech enhancement algorithm to reduce the frequency response. The results show that after using the speech enhancement algorithm, the frequency spectrum correlation coefficient between the reconstructed sinusoidal signal and the original sinusoidal signal is improved by up to 82.45%, and the real speech signal is improved by up to 56.40%. This proves that the speech enhancement algorithm is a valuable tool for solving the frequency response problem and improving the accuracy of reconstructed speech.
“…The narrow line was then extracted from the image, and the strip noise was removed by a smoothing filter. The centroid of each column was calculated using arithmetic mean [31,32,33]. The pixel offset in the time domain could, thus, be obtained.…”
The present study uses a method to address microvibrations effects on an optical satellite by combining simulations and experiments based on high-precision acceleration sensors. The displacement and angular displacement of each optical component can be obtained by introducing flywheel perturbation data from a six-component test bench to the finite element model of the optical satellite. Combined with an optical amplification factor inferred from the linear optical model, the pixel offset of the whole optical system is calculated. A high accuracy and broad frequency range for a new microvibration measurement experimental system is established to validate the simulation. The pixel offset of the whole optical system can be measured by testing the acceleration signals of each optical component and calculating optical amplification factors. The results are consistent with optical imaging test results, indicating correctness of the experimental scheme and the effectiveness of the simulation. The results suggest that the effect of microvibrations on a camera can be verified by using mechanical simulators instead of a whole optical camera for the experiment scheme, which is demonstrated to be an effective way for increasing efficiency in jitter measurements.
“…This pixel-wise coded exposure was implemented by using various techniques, such as spatial light modulators (e.g., a digital micromirror device 35 , 36 and a liquid-crystal-on-silicon device 37 ), a translating printed pattern 38 , 39 , and in-pixel memory in the CMOS architecture 40 . However, the imaging speeds enabled by these methods are clamped to several thousand fps by either the pattern refreshing rates of the spatial light modulators 41 , the moving speed of the piezo stages, or the readout electronics of the imaging sensor. Although CUP provides an ultrafast pixel-wise encoding scheme, its operating principle requires simultaneously shearing the scene and the coded aperture.…”
Single-shot real-time femtophotography is indispensable for imaging ultrafast dynamics during their times of occurrence. Despite their advantages over conventional multi-shot approaches, existing techniques confront restricted imaging speed or degraded data quality by the deployed optoelectronic devices and face challenges in the application scope and acquisition accuracy. They are also hindered by the limitations in the acquirable information imposed by the sensing models. Here, we overcome these challenges by developing swept coded aperture real-time femtophotography (SCARF). This computational imaging modality enables all-optical ultrafast sweeping of a static coded aperture during the recording of an ultrafast event, bringing full-sequence encoding of up to 156.3 THz to every pixel on a CCD camera. We demonstrate SCARF’s single-shot ultrafast imaging ability at tunable frame rates and spatial scales in both reflection and transmission modes. Using SCARF, we image ultrafast absorption in a semiconductor and ultrafast demagnetization of a metal alloy.
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