Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Global Total Variation Minimization
SIAM Journal on Numerical Analysis
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIAM Journal on Scientific Computing
On the Coupled Forward and Backward Anisotropic Diffusion Scheme for Color Image Enhancement
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Adaptive Pre-Filtering Techniques for Colour Image Analysis
IMVIP '07 Proceedings of the International Machine Vision and Image Processing Conference
Efficient and reliable schemes for nonlinear diffusion filtering
IEEE Transactions on Image Processing
Multiresolution segmentation of natural images: from linear to nonlinear scale-space representations
IEEE Transactions on Image Processing
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Data smoothing and feature enhancement are two important precursors to many higher-level computer vision applications such as image segmentation and scene understanding. Total variation (TV) flow algorithms are a distinct subcategory of diffusion-based filtering techniques that have been widely applied to reduce the level of noise in the image but not at the expense of poor feature preservation. In this paper we address a number of numerical aspects associated with the TV flow and in particular we are interested to redefine the TV flow regularization in order to reduce the effect of oscillations and improve the convergence of the implementations in the discrete domain. TV flow algorithms are implemented using iterative schemes and one difficult problem is the selection of appropriate criteria to identify the optimal number of iterations. In this paper we show that the application of a time-ageing procedure leads to an elegant formulation were the TV flow algorithms converge naturally to the optimal solution. To evaluate the performance of the proposed algorithm (referred in this paper to as time-controlled (TC)-TV flow), a large number of experiments on various types of natural images were conducted.