DOUBLE-TIP ARTEFACT REMOVAL FROM ATOMIC FORCE MICROSCOPY IMAGES

CONTACT: PRAVEEN KUMAR. L (, +91 – 9791938249)
MAIL ID: sunsid1989@gmail.com, praveen@nexgenproject.com
Web: www.nexgenproject.com, www.finalyear-ieeeprojects.com
DOUBLE-TIP ARTEFACT REMOVAL FROM ATOMIC FORCE
MICROSCOPY IMAGES
ABSTRACT
The Atomic Force Microscope (AFM) allows the measurement of interactions
at interfaces with nanoscale resolution. Imperfections in the shape of the tip
often lead to the presence of imaging artefacts such as the blurring and
repetition of objects within images. Generally, these artefacts can only be
avoided by discarding data and replacing the probe. Under certain
circumstances (e.g., rare, high value samples, or extensive chemical/physical
tip modification) such an approach is not feasible. Here, we apply a novel
deblurring technique, using a Bayesian framework, to yield a reliable
estimation of the real surface topography without any prior knowledge of the
tip geometry (blind reconstruction). A key contribution is to leverage the
significant recently successful body of work in natural image deblurring to
solve this problem. We focus specifically on the ‘double-tip’ effect, where two
asperities 1 are present on the tip, each contributing to the image formation
mechanism. Finally, we demonstrate that the proposed technique successfully
removes the ‘double-tip’ effect from high resolution AFM images which
demonstrate this artefact whilst preserving feature resolution
CONCLUSIONS

Deconvolution of tip geometry from AFM images is longstanding issue that is
becoming increasingly important as access to high resolution imaging of
challenging biological systems becomes more prevalent. This work focuses on
correcting for the ‘double-tip’ artefact which is a dramatic-form distortion
compared to the traditional tip convolution artefacts. A deblurring model
based on the natural image blurring model was developed for the restoration
of degraded images. A Bayesian deblurring framework containing two key
steps was carried out to recover the true surface topography of the fibrils.
The proposed deblurring framework was successful at removing the ‘double-
tip’ artefacts from AFM images, resulting in a true image of the surface
without sacrificing resolution. Due to the presence of overlapping regions
(resulting from the parallel image formation mechanism) it was not possible
to implement a fully automatic algorithm. A user-interactive process is
incorporated into our deblurring framework which allows the user to provide
information to secure a good estimation of the overlap regions. A new
degraded image is then constructed which satisfies the summation model of
convolution throughout and a Bayesian deconvolution step is applied to
generate restored images with better estimation at the overlap regions. The
restored images demonstrate higher resolution than the original images once
the influence of tip geometry has been removed.
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DOUBLE-TIP ARTEFACT REMOVAL FROM ATOMIC FORCE MICROSCOPY IMAGES

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