By Topic

Image Denoising Using Edge Model-based Representation of Laplacian Subbands

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 $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

3 Author(s)
Malay K. Nema ; CAIR (DRDO), DRDO Complex, Bangalore ; Subrata Rakshit ; Subhasis Chaudhuri

This paper presents a novel method of removing unstructured, spurious artifacts (more popularly called noise) from images. This method uses an edge model-based representation of Laplacian subbands and deals with noise at Laplacian subband levels to reduce it effectively. As the prominent edges are retained in their original form in the denoised images, the proposed method can be classified as an edge preserving denoising scheme. Laplacian subbands are represented using a primitive set (PS) consisting of 7 x 7 subimages of sharp and blurred Laplacian edge elements. The choice of edge model-based representation provides greater flexibility in removing characteristic artifacts from noise sources.

Published in:

Advances in Pattern Recognition, 2009. ICAPR '09. Seventh International Conference on

Date of Conference:

4-6 Feb. 2009