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In today’s highly computerized world, data compression is a key issue to minimize the
costs associated with data storage and transfer. In 2019, more than 70% of the data
sent over the network were images. This paper analyses the feasibility of using the
SVD algorithm in image compression and shows that it improves the efficiency of
JPEG and JPEG2000 compression. Image matrices were decomposed using the SVD
algorithm before compression. It has also been shown that as the image dimensions
increase, the fraction of eigenvalues that must be used to reconstruct the image in
good quality decreases. The study was carried out on a large and diverse set of
images, more than 2500 images were examined. The results were analyzed based on
criteria typical for the evaluation of numerical algorithms operating on matrices and
image compression: compression ratio, size of compressed file, MSE, number of bad
pixels, complexity, numerical stability, easiness of implementation.
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