The growth in number of transistors on a semiconductor chip has followed the Moore's law over the years and simultaneously, the size of transistor has reached equivalent to atomic size. Hence, a novel approach is needed for replacement in CMOS technology. The existing technologies are unable to meet the complex computing challenges due to their inability of inherent parallel processing and adaptability. Hence, there is a need of unconventional methodologies such as quantum computing and neuromorphic computing; and technologies like spintronics to support the realization of these methodologies. Skyrmions are the primary components of skyrmionics, the next generation of spintronics. These are the promising candidates for neuromorphic computing due to their significant features such as topological stability, low driving current density and nanoscale size. In this paper, spintronics based neuromorphic computing has been reviewed and the performance is evaluated in comparison to conventional techniques.
Image restoration of blur and noisy images can be performed in either of the two ways i.e. denoising after deblurring or deblurring after denoising. While performing deblurring after denoising, the residual noise is greatly amplified due to the subsequent deblurring process. In case of denoising after deblurring, the denoising stage severely blurs the image and leads to inadequate restoration. Denoising can be done mainly in two ways namely, linear filtering and non-linear filtering. The former one is fast and easy to implement. However, it produces a serious image blurring. Nonlinear filters can efficiently overcome this limitation and results in highly improved filtering performance but at the cost of high computational complexity. Few filtering algorithms have been proposed for performing image denoising and deblurring simultaneously. This paper presents a novel algorithm for the restoration of blur and noisy images for near real time applications. The proposed algorithm is based on PSF (Point Spread Function) estimation and Wiener filtering. The Wiener filter removes the additive noise and inverts the blurring simultaneously and thus performs an optimal trade-off between inverse filtering and noise suppressing. The Wiener filtering minimizes the overall mean square error in the process of noise suppressing. The PSF used for Wiener filtering is estimated using blind deconvolution. This is a noniterative process and provides faster results.
In digital holographic interferometry (DHI), coherent noise degrades accuracy of phase
information. We present multi-beam polarization DHI in which two cross polarized interferograms are
recorded. Fourier analysis of interferograms reduces coherent noise and increases accuracy.
This paper describes a new and novel phase shifting technique for qualitative as well as quantitative measurement in microscopy. We have developed a phase shifting device which is robust, inexpensive and involves no mechanical movement. In this method, phase shifting is implemented using LED array, beam splitters and defocused projection of Ronchi grating. The light from the LEDs are made incident on the beam splitters at spatially different locations. Due to variation in the geometrical distances of LEDs from the Ronchi grating and by sequentially illuminating the grating by switching on one LED at a time the phase shifted grating patterns are generated. The phase shifted structured patterns are projected onto the sample using microscopic objective lens. The phase shifted deformed patterns are recorded by a CCD camera. The initial alignment of the setup involves a simple procedure for the calibration for equal fringe width and intensity such that the phase shifted fringes are at equal phase difference. Three frame phase shifting algorithm is employed for the reconstruction of the phase map. The method described here is fully automated so that the phase shifted images are recorded just by switching of LEDs and has been used for the shape measurement of microscopic industrial objects. The analysis of the phase shifted images provides qualitative as well as quantitative information about the sample. Thus, the method is simple, robust and low cost compared to PZT devices commonly employed for phase shifting.
We report white light phase shifting interferometry in conjunction with color fringe analysis for the detection of contaminants in water such as Escherichia coli (E.coli), Campylobacter coli and Bacillus cereus. The experimental setup is based on a common path interferometer using Mirau interferometric objective lens. White light interferograms are recorded using a 3-chip color CCD camera based on prism technology. The 3-chip color camera have lesser color cross talk and better spatial resolution in comparison to single chip CCD camera. A piezo-electric transducer (PZT) phase shifter is fixed with the Mirau objective and they are attached with a conventional microscope. Five phase shifted white light interferograms are recorded by the 3-chip color CCD camera and each phase shifted interferogram is decomposed into the red, green and blue constituent colors, thus making three sets of five phase shifted intererograms for three different colors from a single set of white light interferogram. This makes the system less time consuming and have lesser effect due to surrounding environment. Initially 3D phase maps of the bacteria are reconstructed for red, green and blue wavelengths from these interferograms using MATLAB, from these phase maps we determines the refractive index (RI) of the bacteria. Experimental results of 3D shape measurement and RI at multiple wavelengths will be presented. These results might find applications for detection of contaminants in water without using any chemical processing and fluorescent dyes.
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