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Construction model for total variation regularization parameter
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DOI：10.1364/OE.22.010500.png)
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Abstract
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Image denoising is important for high-quality imaging in adaptive optics. Richardson-Lucy deconvolution with total variation(TV) regularization is commonly used in image denoising. The selection of TV regularization parameter is an essential issue, yet no systematic approach has been proposed. A construction model for TV regularization parameter is proposed in this paper. It consists of four fundamental elements, the properties of which are analyzed in details. The proposed model bears generality, making it apply to different image recovery scenarios. It can achieve effective spatially adaptive image recovery, which is reflected in both noise suppression and edge preservation. Simulations are provided as validation of recovery and demonstration of convergence speed and relative mean-square error. (C) 2014 Optical Society of America
Keywords:
TOTAL-VARIATION MINIMIZATION
PHASE-CONTRAST TOMOGRAPHY
RICHARDSON-LUCY ALGORITHM
BLIND DECONVOLUTION
IMAGE-RECONSTRUCTION
FLUORESCENCE
RESTORATION
HOLOGRAPHY
RETRIEVAL
REMOVAL
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3.3
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6.1W
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14.3W
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