Open Access Open Access  Restricted Access Subscription or Fee Access

Two New Methods for Image Compression

El Asnaoui Khalid, Chawki Youness


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.


BTC, image compression, distributed calculation, SVD.

Full Text:



  • There are currently no refbacks.

Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.