Total variation regularized least-squares deconvolution is one of the most standard image processing problems. This package provides an implementation of the current state-of-art algorithm using the concept of augmented Lagrangian , which can be considered as a variation of the popularly known Alternating Direction Methods of Multipliers (ADMM). The user interface of deconvtv is identical to the current MATLAB's deconvolution tools, including deconvwnr, deconvlucy, and deconvreg:
out = deconvtv(img, psf, mu, opt);
deconvtv supports direct space-time processing for both image and video deconvolution problems.
Applications of deconvtv include, and are not limited to: image and video deblurring, image and video denoising, depth data enhancement, hot-air turbulence stabilization, and multi-view synthesis.
For additional information and citations, please refer to:
 S.H. Chan, R. Khoshabeh, K.B. Gibson, P.E. Gill, and T.Q. Nguyen, "An augmented Lagrangian method for total variation video restoration", IEEE Trans. Image Process., vol. 20, no. 11, p. 3097-3111, 2011.
Stanley Chan (2021). deconvtv - fast algorithm for total variation deconvolution (https://www.mathworks.com/matlabcentral/fileexchange/43600-deconvtv-fast-algorithm-for-total-variation-deconvolution), MATLAB Central File Exchange. Retrieved .
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