| Issue |
MATEC Web of Conferences
Volume 54, 2016
2016 7th International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2016)
|
|
|---|---|---|
| Article Number | 08002 | |
| Number of page(s) | 5 | |
| Section | Image processing and visualization | |
| DOI | https://doi.org/10.1051/matecconf/20165408002 | |
| Published online | 22 April 2016 | |
Lossy Image Compression Using PCA and Contourlet Transform
School of Science, Wuhan University of Technology, Wuhan 430070, China
With the rapid development of Internet, image information is growing. It requires a lot of image storage and transmission. In order to reduce the storage and get better image quality, image compression algorithm is studied. The paper proposes a new image compression algorithm that combines principal component analysis (PCA) and Contourlet Transform (CT). Because PCA has good image quality, but the compression ratio is low, and CT compression algorithm has high compression ratio and good PNSR value. The image is decomposed by PCA. The image data is divided into blocks, and each block is used as a sample vector, then select covariance matrix of k larger eigenvalues corresponding eigenvector to realize image compression. Then the image is compressed again using CT compression algorithm. Compared with the results of JEPG2000 and CT compression algorithm, the results show that the proposed algorithm has better performance than JEPG2000 and CT compression algorithm. In the same compression ratio, PNSR value of proposed algorithm is about 3dB higher than that of JEPG2000, and 2dB higher than that of CT compression algorithm.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.