Open AccessImage compression using Analytical and Learned Dictionaries
Author(s) -
G. Priyanka,
M. Geetha Priya,
M Harshali,
M. Venu Gopala Rao
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.7.10881
Subject(s) - computer science , artificial intelligence , image compression , data compression , pattern recognition (psychology) , image processing , image (mathematics) , compression (physics) , signal processing , k svd , signal (programming language) , computer vision , digital signal processing , materials science , computer hardware , composite material , programming language
The modern signal and image processing deals with large data such as images and this data deals with complex statistics and high dimensionality. Sparsity is one powerful tool used signal and image processing applications. The mainly used applications are compression and denoising. A dictionary contains information of the signals in the form of coefficients. Recently dictionary learning has emerged for efficient representation of signals. In this paper we study the image compression using both analytical and learned dictionaries. The results show that the effectiveness of learned dictionaries in the application of image compression.