Comparison of restoration methods for turbulence-degraded images

Yang, Tingxiang; Maraev, Anton A.

doi:10.1117/12.2502331

Cited by 2 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Deconvolution is a processing technique to estimate or recover the desired process from the recorded degraded process. As one of the most classic deconvolution approaches, Wiener deconvolution based on Wiener filtering has been widely employed for 1-D signal recovery [23] and 2-D image deblurring from the recorded degraded signals or images with noise [24]. In 1996, Nakamura et al reported a spatial resolution of 0.5 m at 1 km in the ROTDR system.…”

Section: Introductionmentioning

confidence: 99%

Submetric Spatial Resolution ROTDR Temperature Sensor Assisted by Wiener Deconvolution

Zhu

Chen

et al. 2022

Sensors

View full text Add to dashboard Cite

A submetric spatial resolution Raman optical time-domain reflectometry (ROTDR) temperature sensor assisted by the Wiener deconvolution postprocessing algorithm has been proposed and experimentally demonstrated. Without modifying the typical configuration of the ROTDR sensor and the adopted pump pulse width, the Wiener demodulation algorithm is able to recover temperature perturbations of a smaller spatial scale by deconvoluting the acquired Stokes and anti-Stokes signals. Numerical simulations have been conducted to analyze the spatial resolution achieved by the algorithm. Assisted by the algorithm, a typical ROTDR sensor adopting pump pulses of 20 ns width can realize the distributed temperature sensing with a spatial resolution of 0.5 m and temperature accuracy of 1.99 °C over a 2.1-km sensing fiber.

show abstract

Section: Introductionmentioning

confidence: 99%

Submetric Spatial Resolution ROTDR Temperature Sensor Assisted by Wiener Deconvolution

Zhu

Chen

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

Enhancing spatial resolution of BOTDR sensors using image deconvolution

Guo

Feng

et al. 2022

Opt. Express

View full text Add to dashboard Cite

We propose to employ the image deconvolution technique for Brillouin optical time domain reflectometry (BOTDR) systems to achieve a flexible and enhanced spatial resolution with pump pulses longer than phonon lifetime. By taking the measured Brillouin gain spectrum (BGS) distribution as an image blurred by a point spread function (PSF), the image deconvolution algorithm based on the two-dimensional Wiener filtering can mitigate the ambiguity effect on the Brillouin response. The deconvoluted BGS distribution reveals detailed sensing information within shorter fiber segments, improving the inferior spatial resolution and simultaneously maintaining other sensing performance parameters. Thanks to the proposed technique, a typical BOTDR sensor with 40 ns pump pulses reaches a submetric spatial resolution as high as 10 cm. Compared to the differential-spectrum-based BOTDR retrieving the same spatial resolution, the image deconvolution technique shows advantages in system complexity and measurement uncertainty. Moreover, the proposed technique is promising to improve the spatial resolution of other distributed optical fiber sensing (DOFS) techniques such as BOTDR systems with complex pump modulation methods.

show abstract

Comparison of restoration methods for turbulence-degraded images

Cited by 2 publications

References 5 publications

Submetric Spatial Resolution ROTDR Temperature Sensor Assisted by Wiener Deconvolution

Submetric Spatial Resolution ROTDR Temperature Sensor Assisted by Wiener Deconvolution

Enhancing spatial resolution of BOTDR sensors using image deconvolution

Contact Info

Product

Resources

About