The Tapestry Cellular Automata phase unwrapping algorithm for interferogram analysis

Chang, Heui-Yung; Chen, C.W.; Lee, C.K.; Hu, Chenfei

doi:10.1016/s0143-8166(98)00054-2

Cited by 17 publications

(3 citation statements)

References 7 publications

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“…Segmentation, which divides the phase map into many small overlapped segments, has been developed to improve the computational efficiency for phase unwrapping [16,18]. Each segment is first unwrapped independently.…”

Section: Segmentation and Patchingmentioning

confidence: 99%

“…This method needs complex path design strategy in the presence of noise [5] and is not feasible for the measurement of the laterally discontinuous surface. The path-independent methods, including model- [6,7], Bayesian- [8], least-squares- [9], and integration-based [10][11][12][13][14][15][16][17][18], do not require a specially designed path for spatialbased phase unwrapping. However, none of these pathindependent methods can be directly applied to unwrap the phase of laterally discontinuous surfaces because of the narrow, curved regions and the discontinuity among regions.…”

Section: Introductionmentioning

confidence: 99%

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Phase unwrapping for large depth-of-field 3D laser holographic interferometry measurement of laterally discontinuous surfaces

Huang¹,

Shih²,

Ni³

2006

Meas. Sci. Technol.

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A phase unwrapping method is developed to mathematically increase the depth-of-field for the 3D optical measurement of objects with laterally discontinuous surfaces, which contain disconnected high aspect ratio regions. This method is applied for laser holographic interferometry precision measurements. The phase wrap identification at boundary pixels, masking and recovery, dynamic segmentation and phase adjustment are developed to overcome the divergence problem in phase unwrapping of laterally discontinuous surfaces. An automotive automatic transmission valve body is applied as an example to demonstrate the developed method. Experimental results demonstrate that the proposed methods can efficiently unwrap the phase to increase the depth-of-field for laterally discontinuous surfaces. Effects of segment size and width of overlapped regions on the computational efficiency are investigated.

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Section: Segmentation and Patchingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Phase unwrapping for large depth-of-field 3D laser holographic interferometry measurement of laterally discontinuous surfaces

Huang¹,

Shih²,

Ni³

2006

Meas. Sci. Technol.

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show abstract

“…The above three different types of noise easily cause the spatial phase unwrapping algorithms to fail. Generally speaking, the spatial phase unwrapping algorithms can be classified as path-dependent [13], path-independent [14][15][16], or miscellaneous [6,[17][18][19]. In most path-dependent algorithms, they quickly operate the unwrapping paths pixel by pixel and shift the wrapped phase by 2π when the unwrapping paths meet the difference between two neighboring pixels greater than π.…”

Section: Introductionmentioning

confidence: 99%

Modified detection scheme for locating phase jumps and reducing detection errors

Weng

2013

Appl. Opt.

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Most phase unwrapping algorithms shift the 2π phase jump pixels to obtain the unwrapped phases, while most filtering algorithms remove the noisy pixels to avoid the fault of unwrapped phases. Thus, finding the positions of phase jump pixels and noisy pixels is important. This study proposed a modified detection scheme developed from the originally published noise and phase jump detection scheme [Opt. Express 19, 3086 (2011)]. The original detection scheme finds the noise positions and phase jump positions, and then marks these pixels in two maps, namely, the noise map and the phase jump map. One 2π phase jump contains a 2π-high position and a 0-low position. However, the original detection scheme usually finds a 2π-high position and misses a corresponding 0-low position, or usually finds a 0-low position and misses a corresponding 2π-high position. Moreover, the original detection scheme produces detection errors, containing the repeated pixels of phase jump or the wrong pixels generated by noise. Fortunately, the proposed modified detection scheme can find both the 2π-high position and the corresponding 0-low position. Moreover, the detection errors are also reduced by the proposed modified detection scheme. The robustness of the modified detection scheme is demonstrated both numerically and experimentally.

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Filters with Noise/Phase Jump Detection Scheme for Image Reconstruction

Weng

2011

Conference Proceedings of the Society for Experimental Mechanics Series

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The Tapestry Cellular Automata phase unwrapping algorithm for interferogram analysis

Cited by 17 publications

References 7 publications

Phase unwrapping for large depth-of-field 3D laser holographic interferometry measurement of laterally discontinuous surfaces

Phase unwrapping for large depth-of-field 3D laser holographic interferometry measurement of laterally discontinuous surfaces

Modified detection scheme for locating phase jumps and reducing detection errors

Filters with Noise/Phase Jump Detection Scheme for Image Reconstruction

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