Perception enhancement of subthreshold noisy image with vibrational resonance

Morfu, Savério; Usama, B.I.; Marquié, Patrick

doi:10.1049/el.2018.8059

Cited by 10 publications

(4 citation statements)

References 12 publications

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“…Moreover, VR can control SR to achieve better signal enhancement [6]. This phenomenon has attracted considerable interest of many scholars and has been applied to many fields, including nonlinear dynamics [7], liquid crystals [8], biology [9][10][11], optics systems [12,13], nano-electromechanical resonators [14], ecological systems [15], image processing [16,17], signal processing [18][19][20][21], etc.…”

Section: Introductionmentioning

confidence: 99%

Vibrational resonance by using a real-time scale transformation method

Gong¹,

Yang²,

Sanjuán³

et al. 2022

Phys. Scr.

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Vibrational resonance (VR) shows great advantages in signal enhancement. Nonlinear frequency modulated (NLFM) signals widely exist in various fields，so it is of great significance to enhance a NLFM signal. However, for the complex NLFM signal, where its instantaneous frequency of the signal varies nonlinearly, the traditional VR method is no longer applicable. To solve this problem, a rescaled VR method by a real-time scale transformation method is proposed. Its basic principle is to use the real-time scale coefficient and auxiliary signal parameters to match a NLFM signal in a nonlinear system. The corresponding numerical simulation is carried out to process three kinds of typical NLFM signals. The results manifest the excellent performance of the proposed method for the signal enhancement of NLFM signals. The method can process NLFM signals with an arbitrary frequency variation. Consequently, it has certain theoretical and practical values in some fields.

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Section: Introductionmentioning

confidence: 99%

Vibrational resonance by using a real-time scale transformation method

Gong¹,

Yang²,

Sanjuán³

et al. 2022

Phys. Scr.

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“…However, contrary to SR applications [6,22], we must admit that very few studies have extended the applications of VR to two-dimensional signals [23–27], i.e. images [28]. In this paper, we propose to explore such applications in the image processing field.…”

Section: Introductionmentioning

confidence: 99%

On some applications of vibrational resonance on noisy image perception: the role of the perturbation parameters

Morfu¹,

Usama²,

Marquié³

2021

Phil. Trans. R. Soc. A.

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In this paper, we first propose a brief overview of nonlinear resonance applications in the context of image processing. Next, we introduce a threshold detector based on these resonance properties to investigate the perception of subthreshold noisy images. By considering a random perturbation, we revisit the well-known stochastic resonance (SR) detector whose best performances are achieved when the noise intensity is tuned to an optimal value. We then introduce a vibrational resonance detector by replacing the noisy perturbation with a spatial high-frequency signal. To enhance the image perception through this detector, it is shown that the noise level of the input images must be lower than the optimal noise value of the SR-based detector. Under these conditions, considering the same noise level for both detectors, we establish that the vibrational resonance (VR)-based detector significantly outperforms the SR-based detector in terms of image perception. Moreover, we show that whatever the perturbation amplitude, the best perception through the VR detector is ensured when the perturbation frequency exceeds the image size. This article is part of the theme issue ‘Vibrational and stochastic resonance in driven nonlinear systems (part 2)’.

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“…Vibrational resonance (VR), firstly reported by Landa & McClintock [1], describes the resonant behaviour of the response of a bistable model to a low-frequency signal by optimizing the amplitude of a high-frequency periodic vibration. This interesting phenomenon, analogous to stochastic resonance [2–5], replaces artificially added noise with high-frequency vibrations, and has received considerable interest in nonlinear dynamics [1,6–16], neuroscience [17–22], engineering [23–27], information processing [28–30], etc. The mechanism of VR is elucidated in different systems with constant mass[1], and also extended to encompass systems with position-dependent mass (PDM) [11].…”

Section: Introductionmentioning

confidence: 99%

Study of vibrational resonance in nonlinear signal processing

Pan

Duan

Chapeau‐Blondeau

et al. 2021

Phil. Trans. R. Soc. A.

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Vibrational resonance (VR) intentionally applies high-frequency periodic vibrations to a nonlinear system, in order to obtain enhanced efficiency for a number of information processing tasks. Note that VR is analogous to stochastic resonance where enhanced processing is sought via purposeful addition of a random noise instead of deterministic high-frequency vibrations. Comparatively, due to its ease of implementation, VR provides a valuable approach for nonlinear signal processing, through detailed modalities that are still under investigation. In this paper, VR is investigated in arrays of nonlinear processing devices, where a range of high-frequency sinusoidal vibrations of the same amplitude at different frequencies are injected and shown capable of enhancing the efficiency for estimating unknown signal parameters or for detecting weak signals in noise. In addition, it is observed that high-frequency vibrations with differing frequencies can be considered, at the sampling times, as independent random variables. This property allows us here to develop a probabilistic analysis—much like in stochastic resonance—and to obtain a theoretical basis for the VR effect and its optimization for signal processing. These results provide additional insight for controlling the capabilities of VR for nonlinear signal processing. This article is part of the theme issue ‘Vibrational and stochastic resonance in driven nonlinear systems (part 1)’.

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Perception enhancement of subthreshold noisy image with vibrational resonance

Abstract: The authors reveal the first evidence of subthreshold noisy image perception, which takes benefit of the vibrational resonance phenomenon. Indeed, an appropriate amount of a high-frequency perturbation allows revealing a grey level noisy image through a threshold detector.

Cited by 10 publications

References 12 publications

Vibrational resonance by using a real-time scale transformation method

Vibrational resonance by using a real-time scale transformation method

On some applications of vibrational resonance on noisy image perception: the role of the perturbation parameters

Study of vibrational resonance in nonlinear signal processing

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