The purpose of this paper is to study an important application of Singular Value Decomposition (SVD) to image processing. The idea is that by using the smaller number of vectors, one can reconstruct an image that is closer to the original. The clarity of the image depends on how many singular values are used to reconstruct it. In this paper, SVD was applied to the image and also using the Matlab software we developed the code. We also demonstrated how the SVD is used to minimize the size needed to store an image.
Keywords
Singular Value Decomposition, Image Compression, Image Processing
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