IMAGE COMPRESSION USING SVD [SINGULAR VALUE DECOMPOSITION]

版本 1.0.0 (1.5 KB) 作者: AMIT SURYAVANSHI
The code is made by using the SVD method that is the singular value decomposition method which is using the U sigma and one more matrix
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更新时间 2024/1/14

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In linear algebra, the Singular Value Decomposition (SVD) of a matrix is a factorization of that matrix into three matrices. It has some interesting algebraic properties and conveys important geometrical and theoretical insights about linear transformations. It also has some important applications in data science. In this article, I will try to explain the mathematical intuition behind SVD and its geometrical meaning. Instead of manual calculations,
i will be using the SVD method by using the function [U S V] =svd (gray_image,'econ') i have done this compression in the white black mode but it was a buttery work for me thanks to the functions present in the matlab

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AMIT SURYAVANSHI (2024). IMAGE COMPRESSION USING SVD [SINGULAR VALUE DECOMPOSITION] (https://www.mathworks.com/matlabcentral/fileexchange/157651-image-compression-using-svd-singular-value-decomposition), MATLAB Central File Exchange. 检索来源 .

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1.0.0