2011 National Conference on Communications (NCC) 2011
DOI: 10.1109/ncc.2011.5734771
|View full text |Cite
|
Sign up to set email alerts
|

Poisson noise removal from images using the fast discrete Curvelet transform

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2012
2012
2015
2015

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 7 publications
0
1
0
Order By: Relevance
“…The localization of the curvelet in position, scale and orientation helps it to provide very close optimal sparse representation of objects which have singularities along smooth curves. The general procedure of mammogram denoising by the fast discrete curvelet transform (FDCT) is explained briefly [12]. The fast Fourier transform (FFT) is used to compute the two dimension (2-D) discrete Fourier transform (DFT) of the input mammogram containing noise.…”
Section: Mammogram Denoising By the Curvelet Transformmentioning
confidence: 99%
“…The localization of the curvelet in position, scale and orientation helps it to provide very close optimal sparse representation of objects which have singularities along smooth curves. The general procedure of mammogram denoising by the fast discrete curvelet transform (FDCT) is explained briefly [12]. The fast Fourier transform (FFT) is used to compute the two dimension (2-D) discrete Fourier transform (DFT) of the input mammogram containing noise.…”
Section: Mammogram Denoising By the Curvelet Transformmentioning
confidence: 99%