By Topic

Semi-adaptive, convex optimisation methodology for image denoising

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
$33 $31
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)
Karkkainen, T. ; Dept. of Math. Inf. Technol., Univ. of Jyvaskyla, Finland ; Majava, K.

An optimisation methodology based on a semi-adaptive, convex (SAC) formulation for the image denoising problem is proposed for recovering both sharp edges and smooth subsurfaces from a given noisy image. Basic steps to realise an image denoising algorithm with proper restoration properties and practical computational efficiency with automatic determination of free parameters are described. A set of example images is used to illustrate the proposed approach.

Published in:

Vision, Image and Signal Processing, IEE Proceedings -  (Volume:152 ,  Issue: 5 )