Browsing by Author "Waghmare, R.G."

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    Effective denoising with non-local means filter for reliable unwrapping of digital holographic interferometric fringes
    (2018) Aparna, P.L.; Waghmare, R.G.; Mishra, D.; Sai, Subrahmanyam, Gorthi, R.K.
    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 (-?, ?]. 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. � 2018, Springer Nature Singapore Pte Ltd.
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    Effective denoising with non-local means filter for reliable unwrapping of digital holographic interferometric fringes
    (Springer Verlag service@springer.de, 2018) Aparna, P.L.; Waghmare, R.G.; Mishra, D.; Sai Subrahmanyam Gorthi, R.K.
    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 (-π, π]. 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. © 2018, Springer Nature Singapore Pte Ltd.