# $rm K$ -SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation

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### Cites background or methods from "$rm K$ -SVD: An Algorithm for Desig..."

...Indeed, we might do better by using a redundant version of the DCT,1 as practiced in [ 36 ]....

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...The K-SVD proposes an iterative algorithm designed to handle the above task effectively [ 36 ], [37]....

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...Instead of supplying an artificial set of examples to train on, as proposed above, one could take the patches from the corrupted image, , where . Since the K-SVD dictionary learning process has in it a noise rejection capability (see experiments reported in [ 36 ]), this seems like a natural idea....

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...K-SVD algorithm [ 36 ], [37] because of its simplicity and efficiency for this task....

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...This way, the value of is guaranteed to drop per an update of each dictionary atom, and along with this update, the representation coefficients change as well (see [ 36 ] and [37] for more details)....

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### Cites background from "$rm K$ -SVD: An Algorithm for Desig..."

..., [1]) is to densely extract patches and then represent them by a set of pre-trained bases such as PCA, DCT, Haar, etc....

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2,667 citations

##### References

9,950 citations

### "$rm K$ -SVD: An Algorithm for Desig..." refers background in this paper

...It is in this setting that we ask what the proper dictionary is....

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### "$rm K$ -SVD: An Algorithm for Desig..." refers methods in this paper

...There is an interesting relation between the above method and the independent component analysis (ICA) algorithm [43]....

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7,015 citations

### "$rm K$ -SVD: An Algorithm for Desig..." refers background or methods in this paper

...We then discuss some of the -SVD properties and implementation issues....

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...There is a variant of the vector quantization (VQ) coding method, called gain-shape VQ, where this coefficient is allowed to vary [39]....

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