Open AccessA singular value decomposition based approach for the compression of encrypted images
Author(s) -
Hiyam Hatem,
Raed Majeed,
Jumana Waleed
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.12707
Subject(s) - singular value decomposition , encryption , redundancy (engineering) , discrete wavelet transform , random permutation , computer science , wavelet , image compression , pyramid (geometry) , compression (physics) , singular value , algorithm , wavelet transform , data compression , artificial intelligence , image (mathematics) , mathematics , computer vision , image processing , materials science , block (permutation group theory) , eigenvalues and eigenvectors , geometry , physics , composite material , quantum mechanics , operating system
Image compression is a process which supplies a good solution to the current problems of data storage by reducing redundancy, and irrelevance within images. This paper provides effective encryption then compression technique applied for compressing images within the entire domain of encryption. The Singular Value Decomposition (SVD) application has been described for the results of compression from an image encrypted based on Discrete wavelet transforms (DWT). Initially, the original image has been decomposed into a pyramid of wavelet by utilizing DWT. The DWT subbands are enciphered via a pseudo random number and pseudo random permutation. Then, encrypted images are compressed evaluated by the SVD method which encompasses the corresponding singular values and singular vectors. The performance evaluated on several images and the experimental results and security evaluation is given to validate the explained goals of high security and good compression performance.