Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Fast and high performance image subsampling using feedforward neural networks

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)
Dumitras, A. ; Dept. of Electr. & Comput. Eng., British Columbia Univ., Vancouver, BC, Canada ; Kossentini, F.

We introduce a fast and high performance image subsampling method using feedforward artificial neural networks (FANNs). Our method employs a pattern matching technique to extract local edge information within the image, in order to select the FANN desired output values during the supervised training stage. Subjective and objective evaluations of experimental results using still images and video frames show that our method, while less computationally intensive, outperforms the standard lowpass filtering and subsampling method

Published in:

Image Processing, IEEE Transactions on  (Volume:9 ,  Issue: 4 )