Two New Methods for Image Compression
The problem that we consider in this paper is about the compression of images in a large database. In this context, we propose two improved algorithms: The first is an improvement of the Block Truncation Coding method that overcomes the disadvantages of the classical Block Truncation Coding which uses sequential calculations, and the problem related to the processing of the original image borders, while the second describes how to obtain a new rank of SVD method, this one shows the new rank to approximate an image using the least amount of information. By comparing the performances of the two algorithms to several methods in state of the art, we will show that the first one presents several advantages; it is fast, reduces memory consuming and it doesnt require learning. The second method shows a better image compression. To validate our results, these algorithms will be applied to different real images in a database.
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