Results 1 - 10 of 76

Image cartoon-texture decomposition and feature selection using the total variation regularized L 1 functional

by Wotao Yin, Donald Goldfarb, Stanley Osher , 2006
"... Abstract. This paper studies the model of minimizing total variation with an L 1-norm fidelity term for decomposing a real image into the sum of cartoon and texture. This model is also analyzed and shown to be able to select features of an image according to their scales. 1 ..."
Abstract - Cited by 24 (4 self) - Add to MetaCart
Abstract. This paper studies the model of minimizing total variation with an L 1-norm fidelity term for decomposing a real image into the sum of cartoon and texture. This model is also analyzed and shown to be able to select features of an image according to their scales. 1

The total variation regularized L 1 model for multiscale decomposition

by Wotao Yin, Donald Goldfarb, Stanley Osher , 2006
"... This paper studies the total variation regularization model with an L 1 fidelity term (TV-L 1) for decomposing an image into features of different scales. We first show that the images produced by this model can be formed from the minimizers of a sequence of decoupled geometry subproblems. Using th ..."
Abstract - Cited by 7 (1 self) - Add to MetaCart
This paper studies the total variation regularization model with an L 1 fidelity term (TV-L 1) for decomposing an image into features of different scales. We first show that the images produced by this model can be formed from the minimizers of a sequence of decoupled geometry subproblems. Using

Imaging with Kantorovich-Rubinstein discrepancy

by Jan Lellmann, Dirk A. Lorenz, Tuomo Valkonen , 2014
"... We propose the use of the Kantorovich-Rubinstein norm from optimal transport in imaging problems. In particular, we discuss a variational regularisation model endowed with a Kantorovich-Rubinstein discrepancy term and total variation regularization in the context of image denoising and cartoon-textu ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
We propose the use of the Kantorovich-Rubinstein norm from optimal transport in imaging problems. In particular, we discuss a variational regularisation model endowed with a Kantorovich-Rubinstein discrepancy term and total variation regularization in the context of image denoising and cartoon-texture

Automated regularization parameter selection in multi-scale total variation models for image restoration

by Yiqiu Dong, M. Monserrat Rincon-camacho - Journal of Mathematical Imaging and Vision
"... Abstract. A multi-scale total variation model for image restoration is introduced. The model utilizes a spatially dependent regularization parameter in order to enhance image regions containing details while still sufficiently smoothing homogeneous features. The fully automated adjustment strategy o ..."
Abstract - Cited by 11 (2 self) - Add to MetaCart
Abstract. A multi-scale total variation model for image restoration is introduced. The model utilizes a spatially dependent regularization parameter in order to enhance image regions containing details while still sufficiently smoothing homogeneous features. The fully automated adjustment strategy

FAST DUAL MINIMIZATION OF THE VECTORIAL TOTAL VARIATION NORM AND APPLICATIONS TO COLOR IMAGE PROCESSING

by X. Bresson, T. F. Chan , 2008
"... Abstract. We propose a regularization algorithm for color/vectorial images which is fast, easy to code and mathematically well-posed. More precisely, the regularization model is based on the dual formulation of the vectorial Total Variation (VTV) norm and it may be regarded as the vectorial extensio ..."
Abstract - Cited by 52 (2 self) - Add to MetaCart
Abstract. We propose a regularization algorithm for color/vectorial images which is fast, easy to code and mathematically well-posed. More precisely, the regularization model is based on the dual formulation of the vectorial Total Variation (VTV) norm and it may be regarded as the vectorial

PREPRINT 1 Texture Enhanced Histogram Equalisation Using TV-L 1 Image Decomposition

by Ovidiu Ghita, Dana E. Ilea, Paul F. Whelan, Senior Member
"... Abstract — Histogram transformation defines a class of image processing operations that are widely applied in the implementation of data normalisation algorithms. In this paper we present a new variational approach for image enhancement that has been constructed to alleviate the intensity saturation ..."
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saturation effects that are introduced by standard contrast enhancement methods based on histogram equalisation. In our work we initially apply total variation (TV) minimisation with a L 1 fidelity term to decompose the input image with respect to cartoon and texture components. Contrary to previous works

SCALE-DRIVEN IMAGE DECOMPOSITION WITH APPLICATIONS TO RECOGNITION, REGISTRATION, AND SEGMENTATION

by Terrence Chen
"... In this paper, we propose to solve several computer vision problems using a novel fundamental idea, the scale difference between different patterns. In order to achieve our goal, we utilize the recently proposed total variation regularized L1 functional, which has an unique geometric feature of deco ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
In this paper, we propose to solve several computer vision problems using a novel fundamental idea, the scale difference between different patterns. In order to achieve our goal, we utilize the recently proposed total variation regularized L1 functional, which has an unique geometric feature

2 NONMONOTONE BARZILAI-BORWEIN GRADIENT ALGORITHM FOR ℓ1-REGULARIZED NONSMOOTH MINIMIZATION IN COMPRESSIVE SENSING

by unknown authors
"... ar ..."
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Abstract not found

Variational denoising of partly textured images by spatially varying constraints

by Guy Gilboa, Nir Sochen, Yehoshua Y. Zeevi - IEEE Trans. IP , 2006
"... Abstract—Denoising algorithms based on gradient dependent regularizers, such as nonlinear diffusion processes and total variation denoising, modify images towards piecewise constant functions. Although edge sharpness and location is well preserved, important information, encoded in image features li ..."
Abstract - Cited by 14 (0 self) - Add to MetaCart
Abstract—Denoising algorithms based on gradient dependent regularizers, such as nonlinear diffusion processes and total variation denoising, modify images towards piecewise constant functions. Although edge sharpness and location is well preserved, important information, encoded in image features

Active Mask Framework for Segmentation of Fluorescence Microscope Images

by Gowri Srinivasa, Advisor Prof, Prof Matthew, C. Fickus, Prof Adam, D. Linstedt, Prof Robert, F. Murphy
"... m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol of ..."
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m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol
Results 1 - 10 of 76