Proceedings ArticleDOI
Phase unwrapping with Kalman filter based denoising in digital holographic interferometry
P. Ram Sukumar,Rahul G. Waghmare,Rakesh Kumar Singh,Gorthi R. K. Sai Subrahmanyam,Deepak Mishra +4 more
- pp 2256-2260
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TLDR
This paper discusses a Fourier transform based phase unwrapping method that is highly robust to noise and performs better even at lower SNR values (5-10dB) with a very less value of RMS error.Abstract:
Phase information recovered through interferometric techniques is mathematically wrapped in the interval (−π, π). Obtaining the original unwrapped phase is very important in numerous number of applications. This paper discusses a Fourier transform based phase unwrapping method. Kalman filter is proposed for denoising in post processing step to restore the unwrapped phase without any noise. The proposed method is highly robust to noise and performs better even at lower SNR values (5–10dB) with a very less value of RMS error. Also, the time taken for execution is very less compared to the many available methods in the literature.read more
Citations
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Two Dimensional Phase Unwrapping Theory Algorithms And Software
TL;DR: Two-dimensional phase unwrapping algorithms applied to feminist theory crime and social justice theoretical conscience volume 4 dr-caloriez henry and the paper route cafebr chapter 3 what is money mishkin cafebr.
Proceedings ArticleDOI
A Deep Learning-based Model for Phase Unwrapping
TL;DR: This is the first work that uses convolutional neural network for phase unwrapping, and this will hopefully pave the way to a new class of techniques for unwrapped the phase.
Posted Content
A Joint Convolutional and Spatial Quad-Directional LSTM Network for Phase Unwrapping
Malsha V. Perera,Ashwin De Silva +1 more
TL;DR: This paper introduces a novel Convolutional Neural Network that incorporates a Spatial Quad-Directional Long Short Term Memory (SQD-LSTM) for phase unwrapping, by formulating it as a regression problem.
Proceedings ArticleDOI
An improved online denoising algorithm based on Kalman filter and adaptive current statistics model
TL;DR: The results show that the proposed self-adaptive adjustment algorithm of measurement variance by means of introducing forgetting factor to estimate ‘R’ can achieve the favorable denoising effect and be convergent to the real value.
Book ChapterDOI
Effective Denoising with Non-local Means Filter for Reliable Unwrapping of Digital Holographic Interferometric Fringes
TL;DR: This paper proposes a preprocessing technique that removes the noise from the interference field, thereby improving the performance of naive unwrapping algorithms and validates the applicability of proposed approach for processing the noisy interference field.
References
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Book ChapterDOI
A New Approach to Linear Filtering and Prediction Problems
TL;DR: In this paper, the clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the?stat-tran-sition? method of analysis of dynamic systems.
Journal ArticleDOI
Satellite radar interferometry: Two-dimensional phase unwrapping
TL;DR: In this paper, an approach to 'unwrapping' the 2 pi ambiguities in the two-dimensional data set is presented, where it is found that noise and geometrical radar layover corrupt measurements locally, and these local errors can propagate to form global phase errors that affect the entire image.
Book
Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software
Dennis C. Ghiglia,Mark D. Pritt +1 more
TL;DR: Methods for Phase Unwrapping, Phase Data, Quality Maps, Masks, and Filters, and Minimum-Norm Methods.
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