Paper Info
Title
Improved Non-Local Means Algorithm Based On Dimensionality Reduction
Abstract
Non-Local Means is an image denoising algorithm based on patch similarity. It compares a reference patch with the neighboring patches to find similar patches. Such similar patches participate in the weighted averaging process. Most of the computational time for Non-Local Means scheme is consumed to measure patch similarities. In this paper, we have proposed an improvement where the image patches are projected into a global feature space. Then we have performed a statistical t-test to reduce the dimensionality of this feature space. Denoising is achieved based on this reduced feature space. The proposed modification exploits an improvement in terms of denoising performance and computational time.
Year
DOI
Venue
2015
10.1007/978-3-319-20801-5_5
IMAGE ANALYSIS AND RECOGNITION (ICIAR 2015)
Keywords
Field
DocType
Non-Local Means algorithm, Image denoising, Image smoothing, Image enhancement, Additive white Gaussian noise, Spatial domain filtering
Noise reduction,Feature vector,Dimensionality reduction,Pattern recognition,Non-local means,Computer science,Algorithm,Curse of dimensionality,Artificial intelligence,Image restoration,Gaussian noise,Additive white Gaussian noise
Conference
Volume
ISSN
Citations 
9164
0302-9743
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
golam morshed maruf120.69
Mahmoud R. El-Sakka28114.17