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[PDF] Top 20 Learning A Tree-Structured Dictionary For Efficient Image Representation With Adaptive Sparse Coding

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Learning A Tree-Structured Dictionary For Efficient Image Representation With Adaptive Sparse Coding

Learning A Tree-Structured Dictionary For Efficient Image Representation With Adaptive Sparse Coding

... send a few pairs of atom index and coefficient value. Recently, tree-structured dictionaries appeared [6, 7, ...the tree is considered as a unique dictionary, each node ... Voir le document complet

6

Learning an Adaptive Dictionary Structure for Efficient Image Sparse Coding

Learning an Adaptive Dictionary Structure for Efficient Image Sparse Coding

... test image is reconstructed for several sparsity values using the learned dictionaries ...DCT dictionary is clearly below the learned dictionaries in terms of quality of ...The tree structure, ... Voir le document complet

5

K-WEB: Nonnegative dictionary learning for sparse image representations

K-WEB: Nonnegative dictionary learning for sparse image representations

... of a 2-step procedure, which is summarized in Algorithm ...the dictionary D is initialized (usually with random values or by taking k random vectors from the input data set), two steps are iter- ated ... Voir le document complet

6

Motion Estimation in Echocardiography Using Sparse Representation and Dictionary Learning

Motion Estimation in Echocardiography Using Sparse Representation and Dictionary Learning

... contrast with 2D imagery, 3D UI is affected by the problems of frame rate and image spatial resolution in the azimuthal direction and thus, does not necessarily provide better motion estimation ... Voir le document complet

15

Denoising and fast diffusion imaging with physically constrained sparse dictionary learning

Denoising and fast diffusion imaging with physically constrained sparse dictionary learning

... Sparse coding has been used to speed up structural MRI acquisition (Ravishankar and Bresler, ...time sparse coding is used on raw DWI with a model that takes into account ... Voir le document complet

35

A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning

A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning

... propose a distributed Frank-Wolfe (dFW) algo- rithm, a novel approach to solve such distributed sparse learning problems based on an adaptation of its central- ized counterpart [20, 21, ...in ... Voir le document complet

10

Automatic Feature Learning for spatio-spectral image classification with sparse SVM

Automatic Feature Learning for spatio-spectral image classification with sparse SVM

... experiments, a preference on the spectral wavelength useful to discriminate this class did not ...ambiguity with the other densely vegetated class, such as the ‘Woodlands’, which is detailed in the second ... Voir le document complet

15

A binary tree-structured MRF model for multispectral satellite image segmentation

A binary tree-structured MRF model for multispectral satellite image segmentation

... The example of Fig.17 illustrates this problem: in a we have a synthetic image with three distinct regions; because only binary segmentations are possible, it can happen given the data m[r] ... Voir le document complet

53

Learning a fast transform with a dictionary

Learning a fast transform with a dictionary

... handy for global ...issues, a scalar weight λ is intro- duced and kernels are constrained to have a unit ...elect a block-coordinate formulation in order to solve the problem with ... Voir le document complet

4

On The Sample Complexity Of Sparse Dictionary Learning

On The Sample Complexity Of Sparse Dictionary Learning

... log n n with high probability. The sample complexity results achieved in this paper recover those of [6, 7] for a different choice of sparsity measure. We suspect that the achieved re- sults can be ... Voir le document complet

5

Astronomical Image Denoising Using Dictionary Learning

Astronomical Image Denoising Using Dictionary Learning

... holds for all astrophysical domains, from the study of the sun through cos- mic microwave background (CMB) analysis ( Starck & Murtagh 2006 ...an image can be decomposed into components at different ... Voir le document complet

15

Indian Buffet process dictionary learning for image inpainting

Indian Buffet process dictionary learning for image inpainting

... sampling for inference, the problem is solved by sampling alternately D, W and σ ε ...the dictionary can be learnt without setting the size in ad- vance and no parameter tuning is ...both with the ... Voir le document complet

6

Adaptive lifting schemes with a global L1 minimization technique for image coding

Adaptive lifting schemes with a global L1 minimization technique for image coding

... ing a criterion related directly to their respective outputs x (o) j+1 ...optimizing a criterion de- fined at the current ...in a multiresolution representation where the decomposition ... Voir le document complet

5

Dictionary learning based sinogram inpainting for CT sparse reconstruction

Dictionary learning based sinogram inpainting for CT sparse reconstruction

... algorithm for sparse sampling is the iterative total variation (TV) min- imization algorithm which relies on the assumption that the main information of the object being im- aged can be well represented by ... Voir le document complet

11

Learning a fast transform with a dictionary

Learning a fast transform with a dictionary

... as a matrix-vector product con- sidering only the elements of h that belong to its support: The idea is to alternatively solve (P k ) by iterating on ...it for a sta- tionary ...associated ... Voir le document complet

4

Hyperspectral and multispectral image fusion based on a sparse representation

Hyperspectral and multispectral image fusion based on a sparse representation

... and sparse coding ...proposed sparse representation-based fusion algorithm. The reference image considered here as the high spatial and high spectral image is a 128 × 128 ... Voir le document complet

12

Sparse Representation-based Image Deconvolution by iterative Thresholding

Sparse Representation-based Image Deconvolution by iterative Thresholding

... proposed a mirror wavelet basis adapted to capture the singularity of the spectrum of the inverse of ...advocated a hybrid approach coined ForWaRD. Deconvolution methods with sparsity promoting ... Voir le document complet

11

Efficient Visual Tracking via Low-Complexity Sparse Representation

Efficient Visual Tracking via Low-Complexity Sparse Representation

... method for feature ...projection with random matrices, rather than fixed matrices as applied in [9, ...developed a fast sparse solution solver with the accelerated proximal gradient ... Voir le document complet

17

Adaptive Dictionary Learning For Competitive Classification Of Multiple Sclerosis Lesions

Adaptive Dictionary Learning For Competitive Classification Of Multiple Sclerosis Lesions

... process: Sparse cod- ing with fixed D and the dictionary update with fixed ...processed for the re- moval of noise and non-brain ...and image patches of predefined size are ... Voir le document complet

5

Efficient second-order online kernel learning with adaptive embedding

Efficient second-order online kernel learning with adaptive embedding

... γ for optimal performance, as that would require multiple runs, and violate the online ...interfere with the gradient descent, and even a small non-adaptive embedding can capture the geometry ... Voir le document complet

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