Standard Framework for Total Variation Denoising
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Total Variation Denoising has emerged as a classical approach for image noise removal. This article presents a MATLAB implementation of the standard ROF92 model, featuring numerical optimization using gradient descent methods with regularization parameter tuning. Additionally, we explore Guy Gilboa's Texture Preserving TV Denoising technique [GSZ03], which incorporates texture-preserving operators through advanced variational formulations. This method maintains crucial texture information while enhancing noise reduction performance through adaptive weighting schemes. Both approaches are widely adopted in image processing applications and warrant thorough investigation for their mathematical foundations and practical implementation strategies involving finite difference discretization and iterative solvers.
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