Image Compression via the Singular Value Decomposition

Initializing live version
Download to Desktop

Requires a Wolfram Notebook System

Interact on desktop, mobile and cloud with the free Wolfram Player or other Wolfram Language products.

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


Snapshots


Details

detailSectionParagraph


Feedback (field required)
Email (field required) Name
Occupation Organization
Note: Your message & contact information may be shared with the author of any specific Demonstration for which you give feedback.
Send