Image Compression via the Singular Value Decomposition

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This demonstrates how an image can be compressed via the singular value decomposition (SVD). The original image is first represented as a matrix with the intensity of each pixel assigned a numeric value. Then the singular value decomposition is performed and a low rank approximation of is formed via , where is the singular value and and are the left and right singular vectors, respectively.

Contributed by: Chris Maes (March 2011)
Open content licensed under CC BY-NC-SA




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