The combination of air-puff systems with real-time corneal imaging (i.e. Optical Coherence Tomography (OCT), or Scheimpflug) is a promising approach to assess the dynamic biomechanical properties of the corneal tissue in vivo. In this study we present an experimental system which, together with finite element modeling, allows measurements of corneal biomechanical properties from corneal deformation imaging, both ex vivo and in vivo. A spectral OCT instrument combined with an air puff from a non-contact tonometer in a non-collinear configuration was used to image the corneal deformation over full corneal cross-sections, as well as to obtain high speed measurements of the temporal deformation of the corneal apex. Quantitative analysis allows direct extraction of several deformation parameters, such as apex indentation across time, maximal indentation depth, temporal symmetry and peak distance at maximal deformation. The potential of the technique is demonstrated and compared to air-puff imaging with Scheimpflug. Measurements ex vivo were performed on 14 freshly enucleated porcine eyes and five human donor eyes. Measurements in vivo were performed on nine human eyes. Corneal deformation was studied as a function of Intraocular Pressure (IOP, 15-45 mmHg), dehydration, changes in corneal rigidity (produced by UV corneal cross-linking, CXL), and different boundary conditions (sclera, ocular muscles). Geometrical deformation parameters were used as input for inverse finite element simulation to retrieve the corneal dynamic elastic and viscoelastic parameters. Temporal and spatial deformation profiles were very sensitive to the IOP. CXL produced a significant reduction of the cornea indentation (1.41x), and a change in the temporal symmetry of the corneal deformation profile (1.65x), indicating a change in the viscoelastic properties with treatment. Combining air-puff with dynamic imaging and finite element modeling allows characterizing the corneal biomechanics in-vivo.
Wavefront coding (WFC) is a powerful hybrid optical-numerical technique for increasing the depth of focus of imaging
systems. It is based on two components: (1) an optical phase element that codifies the wavefront, and (2) a numerical
deconvolution algorithm that reconstructs the image. Traditionally, some sophisticated optical WFC designs have been
used to obtain approximate focus-invariant point spread functions (PSFs). Instead, we present a simple and low cost
solution, implemented on infrared (IR) cameras, which uses a decentred lens inducing coma as an adjustable and
removable phase element. We have used an advanced deconvolution algorithm for the image reconstruction, which is
very robust against high noise levels. These features allow its application to low cost imaging systems. We show
encouraging preliminary results based on realistic simulations using optical PSFs and noise power spectral density (PSD)
laboratory models of two IR imaging systems. Without induced optical phase, the reconstruction algorithm improves the
image quality in all cases, but it performs poorly when there are both in and out-of-focus objects in the scene. When
using our coding/decoding scheme with low-noise detectors, the proposed solution provides high quality and robust
recovery even for severe defocus. As sensor noise increases, the image suffers a graceful degradation, its quality being
still acceptable even when using highly noisy sensors, such as microbolometers. We have experienced that the amount of
induced coma is a key design parameter: while it only slightly affects the in-focus image quality, it is determinant for the
final depth of focus.
In this paper, a decision support system for ship identification is presented. The system receives as input a silhouette of the vessel to be identified, previously extracted from a side view of the object. This view could have been acquired with imaging sensors operating at different spectral ranges (CCD, FLIR, image intensifier). The input silhouette is preprocessed and compared to those stored in a database, retrieving a small number of potential matches ranked by their similarity to the target silhouette. This set of potential matches is presented to the system operator, who makes the final ship identification. This system makes use of an evolved version of the Curvature Scale Space (CSS) representation. In the proposed approach, it is curvature extrema, instead of zero crossings, that are tracked during silhouette evolution, hence improving robustness and enabling to cope successfully with cases where the standard CCS representation is found to be unstable. Also, the use of local curvature was replaced with the more robust concept of lobe concavity, with significant additional gains in performance. Experimental results on actual operational imagery prove the excellent performance and robustness of the developed method.
KEYWORDS: Modulation transfer functions, Signal to noise ratio, Image intensifiers, Electrons, Visualization, Photons, Image processing, Cameras, Transmittance, Night vision
The most straightforward way to describe the performance of an image intensifier tube, especially under adverse conditions, is to predict the image it yields. In this work we have developed two different methods to provide realistic simulated images in low light level conditions: 1) Approximate Physical Model. A classical approach based on the simulation of the different degradation sources. It provides a good understanding of the image formation process. 2) Synthesis-by-analysis of real images. The observed noise is modelled through texture analysis tools and the image blur through the MTF. The resulting simulated images for both methods were compared with real intensified images (laboratory chart sights and natural images) taken under controlled conditions, close to the performance limits of the image intensifier tube. Both methods generated good results in terms of visual comparison for different object sizes, contrasts or luminances. These methods can be used as a new tool to predict the performance thresholds of the image intensifier. Only well-known or measurable parameters were used as input for the methods.
Despite MTF is widely accepted as the most complete figure of merit describing optical quality of image intensifier tubes(IIs), it is not well-established neither in industrial nor governmental testing laboratories. This work aims to advance in the standardization of MTF testing procedures for modern IIs. A versatile device to measure MTF of IIs, based on different FFT related methods, was successfully developed and tested. Several stimuli (slits, 3 and 15 bar targets, random targets) were integrated in the system. Novel algorithms with adaptive parameter selection were developed for windowing, background thresholding, stimulus tilt correction, focusing, spatio-temporal denoising, normalization and scaling. All the methods used were simulated before measurement implementation. The measurement of the MTF of the system with the different methods provides the same result, validating the methods. Measurements on two reference tubes showed that the MTF is sensitive to image quality differences, even with similar limiting resolution. Gain control, halo and luminance influence need further research. The results reported are useful to advance in finding a definitive standard method for measuring IIs MTF.
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