Computational methods to produce enhanced images out of given SNOM raw data

We propose to produce enhanced images out of given raw data read out by SNOM through (i) improved image formation from the raw data; (ii) wavelet de-noising of the image; and (iii) resolution enhancement by deconvolution. Our methods of improvement are based on refined models for the reduction of no...

Full description

Saved in:
Bibliographic Details
Published in:Ultramicroscopy 2005-03, Vol.102 (4), p.299-310
Main Authors: Kiendl, F., Güntherodt, G.
Format: Article
Language:English
Subjects:
Deconvolution
Image formation
SNOM
Wavelet de-noising
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We propose to produce enhanced images out of given raw data read out by SNOM through (i) improved image formation from the raw data; (ii) wavelet de-noising of the image; and (iii) resolution enhancement by deconvolution. Our methods of improvement are based on refined models for the reduction of noise present in SNOM images and on a linear model for the imaging process. They are successfully demonstrated on (magneto-)optical SNOM images of suitable test samples, but yet they are applicable to other scanning probe microscopy techniques.
ISSN:0304-3991
1879-2723
DOI:10.1016/j.ultramic.2004.10.010