KEYWORDS: Image restoration, Modulation, Double patterning technology, Raster graphics, Light scattering, Super resolution, Optical transfer functions, Microscopy, Spatial light modulators, Digital image processing, Digital micromirror devices, Data acquisition, Diffraction, Digital signal processing, Computing systems
Superresolution image reconstruction method based on the structured illumination microscopy (SIM) principle with reduced and simplified pattern set is presented. The method described needs only 2 sinusoidal patterns shifted by half a period for each spatial direction of reconstruction, instead of the minimum of 3 for the previously known methods. The method is based on estimating redundant frequency components in the acquired set of modulated images. Digital processing is based on linear operations. When applied to several spatial orientations, the image set can be further reduced to a single pattern for each spatial orientation, complemented by a single non-modulated image for all the orientations. By utilizing this method for the case of two spatial orientations, the total input image set is reduced up to 3 images, providing up to 2-fold improvement in data acquisition time compared to the conventional 3-pattern SIM method. Using the simplified pattern design, the field of view can be doubled with the same number of spatial light modulator raster elements, resulting in a total 4-fold increase in the space-time product. The method requires precise knowledge of the optical transfer function (OTF). The key limitation is the thickness of object layer that scatters or emits light, which requires to be sufficiently small relatively to the lens depth of field. Numerical simulations and experimental results are presented. Experimental results are obtained on the SIM setup with the spatial light modulator based on the 1920x1080 digital micromirror device.
A new method for precise subpixel edge estimation is presented. The principle of the method is the iterative image
approximation in 2D with subpixel accuracy until the appropriate simulated is found, matching the simulated and
acquired images. A numerical image model is presented consisting of three parts: an edge model, object and background
brightness distribution model, lens aberrations model including diffraction. The optimal values of model parameters are
determined by means of conjugate-gradient numerical optimization of a merit function corresponding to the L2 distance
between acquired and simulated images. Computationally-effective procedure for the merit function calculation along
with sufficient gradient approximation is described. Subpixel-accuracy image simulation is performed in a Fourier
domain with theoretically unlimited precision of edge points location. The method is capable of compensating lens
aberrations and obtaining the edge information with increased resolution. Experimental method verification with digital
micromirror device applied to physically simulate an object with known edge geometry is shown. Experimental results
for various high-temperature materials within the temperature range of 1000°C..2400°C are presented.
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