Sparse Representation
Fingerprint Compression using Sparse Representation
... Biometric identification systems are in use for last many years for the purpose of personal identification, i.e., to associate a particular individual with an identity. Typical application includes security systems, ...
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Image Inpainting Based on Sparse Representation with Histogram Dictionary
... Abstract: This paper proposes a novel image inpainting algorithm based on sparse representation with histogram dictionary. In the propose method, it is a patch-based inpainting method, a patch as the basic ...
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Supervised classification via constrained subspace and tensor sparse representation
... (Sparse Representation Classifier) represents each query sample by a linear sum of a few highly associated training ...a sparse solution of an underdetermined linear ...
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Face recognition based on improved Retinex and sparse representation
... Face recognition via sparse representation (SRC) was first proposed by Wright et al. in 2008, by using its discriminate characteristic to achieve the classification of different person. In previous work ...
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Sparse representation based hyperspectral image compression and classification
... Sparse representation models a set of data based on dictionary and sparse coding. The dictionary is learned in a way that adapts well to the data, and a sample in the data can be represented by just ...
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Reverse Sparse Representation for Single Image Super-Resolution
... reverse sparse representation constraints on Yang's sparse representation model ...reverse sparse representations bridge the HR and LR dictionaries, which reduces the weaknesses of the ...
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DOA estimation of wideband signals based on slice-sparse representation
... slice-sparse representation model of the joint narrowband array covariance data is proposed in the frequency domain to enforce joint sparsity in the concatenated covariance matrix of all ...
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SSIM-inspired image restoration using sparse representation
... super-resolution to improve two state-of-the-art algo- rithms in these areas. We proposed an algorithm to solve for the optimal coefficients for sparse and redun- dant dictionary in maximal SSIM sense. We also ...
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Image similarity using sparse representation and compression distance
... where the dictionary D ∈ R m×n and its columns are the basis functions or atoms. If the values of the majority of components in a ∈ R n are 0 (or close to 0), we say that x has a sparse representation ...
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Metasample Based Robust Sparse Representation for Tumor Classification
... Sparse representation (SR) is a new effective method based on -norm minimization of data ...with sparse coefficient, and classify new sample based on the sparse coefficient ...vector. ...
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Pavement crack characteristic detection based on sparse representation
... Pavement crack detection plays an important role in pavement maintaining and management. The three- dimensional (3D) pavement crack detection technique based on laser is a recent trend due to its ability of ...
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Sparse representation utilizing tight frame for phase retrieval
... the sparse repre- sentation regularization for solving inverse ...fine sparse representation for PR ...for sparse repre- sentation regularization is critical for recovering the ...The ...
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Facial Expression Recognition via Kernel Sparse Representation
... including sparse representation-based classification (SRC), the nearest subspace (NS) [18], support vector machines (SVM), K-nearest neighbor (KNN), and the standard radial basis function neural network ...
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Hyperspectral imagery super-resolution by sparse representation and spectral regularization
... We propose a novel hyperspectral super-resolution algo- rithm by utilizing the sparse representation and spectral mixing model. Single hyperspectral image super-resolu- tion is typical ill-posed inverse ...
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Robust Visual Tracking via Appearance Modeling and Sparse Representation
... Abstract—When appearance variation of object, partial occlusion or illumination change in object images occurs, most existing tracking approaches fail to track the target effectively. To deal with the problem, this paper ...
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SAR target recognition based on improved joint sparse representation
... of sparse representation. Exploring the sparse representation for the multiple input signals at the same time is a joint sparse representation problem ...joint sparse ...
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A novel sparse representation algorithm for AIS real time signals
... signal representation is usually based on ‘base expansion’ such as the classical Fourier transform and the wavelet ...signal sparse representation on a redundant dictionary in 1993 ...nal ...
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A Novel Sparse Representation Method of Occluded Images for Face Recognition
... termed Sparse Representation based Classification (SRC) to accurately recognize expressions under these ...its representation as a linear combination of all available training vectors is ...
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CONTENT BASED VIDEO RETRIEVAL BASED ON HDWT AND SPARSE REPRESENTATION
... unique. Sparse decomposition aims to seek for a solution in which as few atoms as possible would contribute in the ...the sparse representation and to find its usefulness in the video retrieval ...
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SAR Image Target Detection Method Based on Sparse Representation
... of sparse representation in ...of sparse representation is becoming more and more ...signal representation theory based on non-redundant orthogonal linear transformation, such as ...
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