Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

Noise removal algorithms

No description
by

Magdalena Rakowska

on 22 October 2013

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of Noise removal algorithms

REVIEW OF METHODS
SCHEDULE
ICA
OPIS METODY KTORA CHCEMY WYBRAC
PROJECT:

DENOISING IMAGES USING STATISTICAL TECHNIQUES

The group:
Katarzyna Koc
Ewa Ardanowska
Magdalena Rakowska
Manuel Lucena Córdoba
Leopoldo Gómez Castillo

DIVISION OF LABOUR
PCA
Principal component analysis

Involves a mathematical procedure
that transforms a number of (possibly)
correlated variables intoa (smaller)
number of uncorrelated variables

ROBUST STATISTIC
robust statistic is resistant to errors in the results, produced by deviations from assumptions (e.g., of normality). This means that if the assumptions are only approximately met, the robust estimator will still have a reasonable efficiency, and reasonably small bias, as well as being asymptotically unbiased, meaning having a bias tending towards 0 as the sample size tends towards infinity.
?
OPIS
THANK YOU FOR YOUR ATTENTION!


See you on November 12th
CHOSEN TECHNOLOGY

Image denoising is a procedure in digital image processing aiming at the removal of noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. The
presence of noise not only produces undesirable visual quality but also lowers the visibility of
low contrast objects. Noise removal is essential in medical
imaging
applications in
order to
enhance
and recover
fine details that
may be hidden
in the data.
language: Matlab
environment: Matlab R2009b
called principal components.
To discover or to reduce the dimensionality of the data set.
To identify new meaningful underlying variables.
Main objectives of principal component analysis :
case study of ICA algorithm
software development
tests preparation
documentation
Full transcript