Book ChapterDOI
Effective Denoising with Non-local Means Filter for Reliable Unwrapping of Digital Holographic Interferometric Fringes
P. L. Aparna,Rahul G. Waghmare,Deepak Mishra,R. K. Sai Subrahmanyam Gorthi +3 more
- pp 13-24
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TLDR
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.Abstract:
Estimation of phase from the complex interference field has become an emerging area of research for last few decades. The phase values obtained by using arctan function are limited to the interval \((-\pi , \pi ]\). Such phase map is known as wrapped phase. The unwrapping process, which produces continuous phase map from the wrapped phase, becomes tedious in presence of noise. In this paper, we propose a preprocessing technique that removes the noise from the interference field, thereby improving the performance of naive unwrapping algorithms. For de-noising of the complex field, real part and imaginary parts of the field are processed separately. Real-valued images (real and imaginary parts) are processed using non-local means filter with non-Euclidian distance measure. The de-noised real and imaginary parts are then combined to form a clean interference field. MATLAB’s unwrap function is used as unwrapping algorithm to get the continuous phase from the cleaned interference field. Comparison with the Frost’s filter validates the applicability of proposed approach for processing the noisy interference field.read more
Citations
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Journal Article
Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry
TL;DR: In this article, a fast Fourier transform method of topography and interferometry is proposed to discriminate between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour generation techniques.
References
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Journal ArticleDOI
Adaptive Noise Smoothing Filter for Images with Signal-Dependent Noise
TL;DR: The adaptive noise smoothing filter is a systematic derivation of Lee's algorithm with some extensions that allow different estimators for the local image variance and its easy extension to deal with various types of signal-dependent noise.
Journal ArticleDOI
Fringe projection techniques: Whither we are?
Sai Siva Gorthi,Pramod Rastogi +1 more
TL;DR: This paper presents a meta-analyses of Fourier-Transform Profilometry and its applications in 3-D Shape Measurement and Surface Profile Measurement for Structured Light Pattern and 4-Core Optical-Fiber.
Journal ArticleDOI
Adaptive speckle filters and scene heterogeneity
A. Lopes,Ridha Touzi,E. Nezry +2 more
TL;DR: The most well known adaptive filters for speckle reduction are analyzed and it is shown that they are based on a test related to the local coefficient of variation of the observed image, which describes the scene heterogeneity.
Journal ArticleDOI
Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based Weights
TL;DR: The proposed filter is an extension of the nonlocal means (NL means) algorithm introduced by Buades, which performs a weighted average of the values of similar pixels which depends on the noise distribution model.
Iterative Weighted Maximum Likelihood Denoising with Probabilistic Patch-Based Weights c 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
TL;DR: In this article, a more general and statistically grounded similarity criterion is proposed which depends on the noise distribution model, and denoising process is expressed as a weighted maximum likelihood estimation problem where the weights are derived in a data-driven way.