In optical systems with quite good correction, the field-dependence of aberrations often can be neglected. In
low performance systems, for the application of deconvolution methods the field-dependence of the point
spread function must be taken into account. However, the number of publications dealing with the topic of
space-variant deconvolution in order to compensate system aberrations is quite low. In this contribution, we
investigate the fundamental difficulty accompanied by space-variant deconvolution, which makes the problem
ill-posed, even in the case of non-vanishing modular transfer functions and the assumption of noise-free
imaging. The spatial frequencies of the image spectrum are mixed depending on the field-dependencies of
the optical aberrations. In general, it is therefore not possible to reconstruct the individual frequencies exactly.
Some discrete examples with a non unique solution are presented. For the 2D case, we will show and investigate
how the most popular algorithms deal with this fundamental problem for different typical types of optical
aberrations. Depending on the aberration, the computational results for those algorithms differ from very good
results to images with artifacts. The Lucy Richardson method, which is often recommended in the case of spaceinvariant
image reconstruction since it may even reconstruct frequencies above the cut off frequency, provides
poor results for unsymmetrical space-variant aberrations like Coma or a simple Tilt. However, we will show
that a simpler method like the Landweber algorithm is better suited to deal with those kinds of aberrations.
In this paper, two image processing approaches are presented, which are used to gain vision feedback for automatic nanohandling inside a Scanning Electron Microscope (SEM). The first one is a vision-based force measurement that makes use of an active contours tracking algorithm for real-time tracking of the bending line of micro- and nanoobjects. With this algorithm, it is possible to calculate applied forces in real-time with respect to the image acquisition time. This approach is validated using a piezo-resistive force sensor. In a second experiment the force applied to a Si nanowire (d ≈ 470 nm) is measured. The second visual measurement approach deals with the calculations of depth information inside an SEM by means of stereoscopic images. Therefore, a new 3D-imaging system that uses a stereo algorithm based on a biologically motivated energy model is proposed. The system provides a sharp and high density disparity map in sub-pixel accuracy and a 3D-plot for the user.
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