A shape-preserving oriented partial differential equation based on a new fidelity term for electronic speckle pattern interferometry fringe patterns denoising

Xu, Wenjun; Tang, Chen; Zheng, Tingyue; Qiu, Yue

doi:10.1016/j.optlastec.2018.01.036

Cited by 7 publications

(3 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the edges of binary patterns are often difficult to precisely distinguish, which reduces the measurement accuracy. The filtering method [16,17,18,19,20,21,22,23,24] is to reduce noise by means of filtering algorithms. Image filtering is a process of restoring noise-free image from noise image, in which the difficulty is how to protect details while reducing noise.…”

Section: Introductionmentioning

confidence: 99%

“…To this end, partial differential equations (PDEs) methods, such as second-order PDEs, total variation (TV), fourth-order PDEs, oriented PDEs (OPDEs), etc., have been applied for filtering electronic speckle pattern interferometry (ESPI) fringe patterns, which makes the filtering only be carried out along the fringe direction. Tang [20,22,23] proposed a second-order single oriented PDEs method to solve the denoising problems for optical interferometry fringes, and then provided various methods that were based on PDEs. Yang [24] put forward an adaptive model combining the TV and fractional-order differentiation filter for such problems.…”

Section: Introductionmentioning

confidence: 99%

“…Yang [24] put forward an adaptive model combining the TV and fractional-order differentiation filter for such problems. The second-order PDEs [20,23,24,25] easily lead to the phenomenon of the staircase effect, while the four-order PDEs [26] can effectively reduce the staircase phenomenon and get more attention and application. Recently, through introducing the controlling speed function, Tang [9] established an adaptive oriented PDEs filtering method for discontinuous optical fringe patterns.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fringe Phase-Shifting Field Based Fuzzy Quotient Space-Oriented Partial Differential Equations Filtering Method for Gaussian Noise-Induced Phase Error

Xue

et al. 2019

Sensors

View full text Add to dashboard Cite

Traditional filtering methods only focused on improving the peak signal-to-noise ratio of the single fringe pattern, which ignore the filtering effect on phase extraction. Fringe phase-shifting field based fuzzy quotient space-oriented partial differential equations filtering method is proposed to reduce the phase error caused by Gaussian noise while filtering. First, the phase error distribution that is caused by Gaussian noise is analyzed. Furthermore, by introducing the fringe phase-shifting field and the theory of fuzzy quotient space, the modified filtering direction can be adaptively obtained, which transforms the traditional single image filtering into multi-image filtering. Finally, the improved fourth-order oriented partial differential equations with fidelity item filtering method is established. Experiments demonstrated that the proposed method achieves a higher signal-to-noise ratio and lower phase error caused by noise, while also retaining more edge details.

show abstract