By Topic

Image compression using principal component neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jianxun Mi ; Inst. of Intelligent Machines, Chinese Acad. of Sci., Beijing, China ; De-Shuang Huang

This paper presents a comparison of three kinds of principal component neural networks, which are used for image compression. Principal component analysis (PCA), which is a statistical processing technique, is used in many engineering and scientific fields. Application of computing principal components includes data compression, pattern recognition and signal processing, etc. In this paper we use it for image compression.

Published in:

Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th  (Volume:1 )

Date of Conference:

6-9 Dec. 2004