Fourier-domain filtering analysis for color-polarization camera demosaicking.

We review Fourier-domain methods for demosaicking Bayer-filter color cameras and monochrome polarization cameras, and then generalize the approach for the quad-Bayer-filter mosaic and for color-polarization cameras. For each of these four mosaic filter types, we provide theoretical expressions for the sampling functions, the Fourier-domain channels, and the linear combination of reconstructed channels (the demosaicking algorithm) needed to estimate the input (presampled) image. A useful advantage of the Fourier-domain approach is that it provides a direct means of visualizing and quantifying when aliasing is likely or unlikely to be present. For the Bayer and quad-Bayer-filter types, we provide simulated images, while for the polarization camera types we provide experimental images and videos to illustrate the algorithm and analyze crosstalk error.

Erratum: Deep convolutional neural networks-based scatterer density and resolution estimators in optical coherence tomography: erratum.

[This corrects the article on p. 168 in vol. 13, PMID: 35154862.].

Phase-shifting determination and pattern recognition using a modified Sagnac interferometer with multiple reflections.

This work has implemented a diverse modification of the Sagnac interferometer to accommodate various measurement requirements, including phase shifting, pattern recognition, and a morphological analysis. These modifications were introduced to validate the adaptability and versatility of the system. To enable phase shifting using the multiple light reflection technique, a half-wave plate (HWP) was utilized with rotations at 0, π/8, π/4, and 3π/8 radians, generating four interference patterns. It is possible to observe a distinct circular fringe width as the polarized light experiences diffraction at the interferometer's output as it travels through a circular aperture with various diameters ranging from 0.4 to 1 mm. Further modifications were made to the setup by inserting a pure glass and a fluoride-doped tin oxide (FTO) transparent substrate into the common path. This modification aimed to detect and analyze a horizontal fringe pattern. Subsequently, the FTO substrate was replaced with a bee leg to facilitate morphology recognition. A deep learning-based image processing technique was employed to analyze the bee leg morphology. The experimental results showed that the proposed scheme succeeded in achieving the phase shift, measuring hole diameters with errors smaller than 1.6%, separating distinct transparent crystals, and acquiring the morphological view of a bee's leg. The method also has successfully achieved an accurate surface area and background segmentation with an accuracy over 87%. Overall, the outcomes demonstrated the potential of proposed interferometers for various applications, and the advantages of the optical sensors were highlighted, particularly in microscopic applications.

Analysis of volumetric 3D reconstruction of lamina cribrosa images from swept-source optical coherence tomography in glaucomatous and healthy subjects.

This study demonstrates the 3D visualization of the lamina cribrosa (LC) structure and its correlation with volumetric data, pore volume, and disc area in glaucomatous and non-glaucomatous eyes. The participant cohort included 65 glaucomatous and 58 non-glaucomatous eyes (13 suspected glaucoma and 45 normal). An ophthalmologist diagnosed glaucoma patients and all subjects were over 18 years old, passed a visual field test, and underwent optical coherence tomography (OCT) examinations. LC images were obtained using the DRI OCT Triton, while optic disc images were obtained from the enface image of the Cirrus HD-OCT 5000. Since LC images alone did not provide clear edge information, we used optic disc images as a reference for edge detection. To achieve this, we employed a fine-tuned model, specifically a pre-trained U-shaped Encoder-Decoder Network with Attention. This model was used to obtain a segmented mask, which was then aligned and utilized to locate the edge of the LC in the LC images. A blood vessel mask was created to remove blood vessels, as they can interfere with the accurate visualization and analysis of LC characteristics. This step allowed for the 3D reconstruction of the LC structure without the presence of blood vessels. Correlations between LC volume, pore volume, and pore volume to LC volume were calculated separately for glaucomatous and non-glaucomatous eyes. We divided the areas for considering the LC structure into three types: overall, quadrants, and 12-clock-hour sectors. Based on the experimental results, we found that the pore volume and pore-to-LC volume were different between glaucoma and normal across all areas considered. In conclusion, this research generated 3D images of the LC from OCT images using computer techniques, showcasing a microstructure that closely resembles the actual LC. Statistical methods were employed to calculate and analyze the differences observed between the two groups of samples.

Deep convolutional neural network-based scatterer density and resolution estimators in optical coherence tomography.

We present deep convolutional neural network (DCNN)-based estimators of the tissue scatterer density (SD), lateral and axial resolutions, signal-to-noise ratio (SNR), and effective number of scatterers (ENS, the number of scatterers within a resolution volume). The estimators analyze the speckle pattern of an optical coherence tomography (OCT) image in estimating these parameters. The DCNN is trained by a large number (1,280,000) of image patches that are fully numerically generated in OCT imaging simulation. Numerical and experimental validations were performed. The numerical validation shows good estimation accuracy as the root mean square errors were 0.23%, 3.65%, 3.58%, 3.79%, and 6.15% for SD, lateral and axial resolutions, SNR, and ENS, respectively. The experimental validation using scattering phantoms (Intralipid emulsion) shows reasonable estimations. Namely, the estimated SDs were proportional to the Intralipid concentrations, and the average estimation errors of lateral and axial resolutions were 1.36% and 0.68%, respectively. The scatterer density estimator was also applied to an in vitro tumor cell spheroid, and a reduction in the scatterer density during cell necrosis was found.

Hybrid nanowires for phase-matching of third-harmonic generation in hyperbolic metamaterial.

We propose a phase-matching technique for third-harmonic generation, called hyperbolic phase matching, that possibly can be achieved by optimal designing and engineering dispersion of hybrid-nanowire hyperbolic metamaterial. We demonstrate phase-matched conditions for two different third-harmonic interacting configurations, which can be created at two optimal incident angles of the pump field. Moreover, each composed hybrid nanowire can enhance third-harmonic generation by using strong field confinement along the metal/dielectric interface due to plasmonic resonance. Finally, conversion efficiencies of transmitted and reflected third-harmonic pulses as a function of incident angle and input pulse intensity are examined by numerical integration of nonlinear birefringent coupled-mode equations. The numerical results validate the idea that, using a combination of phase-matched conditions and pump field confinement, we can achieve a dramatic enhancement of conversion efficiencies of third-harmonic generation.

Compensating for nonlinear dispersion in channeled spectropolarimetry.

All common waveplate materials exhibit nonlinear dispersion of retardance, producing an unwanted chirp in the interference fringes that channeled spectropolarimeters use for heterodyning polarization data. After showing how to quantify this nonlinearity, we survey the common waveplate materials and find that MgF2 has significantly lower nonlinearity than any other available material. We also quantify the degree of crosstalk caused by dispersion nonlinearity and show that, unlike in linear dispersion, the degree of crosstalk depends on the sequence of how the phase calibration is implemented. Regardless of how the calibrated phases have been obtained, shifting each channel to baseband prior to windowing minimizes crosstalk error.

Alignment precision of polarization components.

Recent research publications in the polarization literature have discussed methods of correcting for azimuthal alignment errors of optical elements in postprocessing. However, we show that high angular precision is not difficult to achieve during system alignment, so that postprocessing correction should be unnecessary. We estimate the alignment precision achievable for linear polarizers and waveplates in polarization systems. This shows that using an optical signal model for alignment allows a precision limited by the quality of the optics and detectors rather than the quality of the mechanics, rendering millidegree alignment precision possible with ordinary rotational mounts.

Dielectrophoresis and colloidal phase transitions for ultra-broadband optical limiting.

We demonstrate wavelength-independent optical limiting based on colloidal phase transitions induced by the dielectrophoretic force from focused electromagnetic radiation. The focused radiation acts as an optical trap that increases the particle density. The increased density then leads to a colloidal gas-solid phase transition and an aggregate that effectively blocks the incoming radiation when it passes a threshold power. The process is reversible, with the colloidal particles returning to a homogenous distribution after the incoming radiation is removed. We demonstrate the effect using polystyrene nanoparticles mixed with pluronics and polyethylene glycol polymers in low-concentration KCl salt solutions. We observe the light-induced phase separation under confocal fluorescent microscope, and we provide a proof-of-principle demonstration of optical limiting using a 100 µm thick colloid cell.

Band-edge field enhanced nonlinear cross-polarized wave generation in photonic band-gap structure.

We report on the enhancement of nonlinear cross-polarized wave (XPW) generation in a one-dimensional photonic band-gap structure, which is composed of two periodic arrangements of barium-fluoride and silicon-dioxide through numerical simulations. By detuning the pump-field wavelength to the band-edge position of the photonic band-gap spectrum, the electric field at this wavelength would be resonant and then the field enhancement mechanism arises immediately. Under band-edge field enhancement condition, we found that the conversion efficiencies of XPW generation was implicitly enhanced even without phase-matched condition from the exact angle of crystallographic axis orientation.

Fast fluorescent imaging-based Thai jasmine rice identification with polynomial fitting function and neural network analysis.

With our single-wavelength spectral-imaging-based Thai jasmine rice identification system, we emphasize here that a combination of an appropriate polynomial fitting function on the determined chain code and a well-trained neural network configuration is highly sufficient in achieving a low false acceptance rate (FAR) and a low false rejection rate (FRR). Experimental demonstration shows promising results in identifying our desired Thai jasmine rice from six unwanted rice varieties with FAR and FRR values of 6.2% and 7.1%, respectively. Additional key performances include a much faster identification time of 30.5 s, chemical-free analysis, robustness, and adaptive learning.

Optical parametric amplification in one-dimensional photonic bandgap structures.

In this paper, optical parametric amplification based on the degenerate four-wave mixing principle in a one-dimensional photonic bandgap (PBG) structure has been numerically studied. First, the multiple scale method was introduced to derive a complete set of nonlinear coupled-mode equations for a finite structure with different inhomogeneous nonlinear coefficients than those used in previous works. This finite structure is composed of 680 dielectric layers, which are alternating half-wave/eight-wave films. The wavelengths of the pump, signal, and idler pulses have been determined from the transmission spectrum, which was illustrated by using the transfer matrix method. The parametric interaction of the pump, signal, and idler pulses inside PBG structure has been numerically simulated by using the split-step Fourier transform method. The results of the simulation have shown that the intensities of the signal and idler have exponential growth with respect to the number of layers in the medium. Meanwhile, pump wavevector detuning directly affects the intensities of both pulses due to a band-edge phase-matching condition that might be achieved from only one optimal detuning parameter. Moreover, both the amplification gain and the conversion efficiency of the idler pulse have been shown to be dependent on the bandwidth of the pump pulse spectrum. A very narrow pulse, with a bandwidth much less than the relevant transmission peak, enables the highest amplification and conversion efficiency in this medium because the most efficient phase-matched condition occurs in this situation. Finally, the conversion efficiency grows exponentially with input pump intensity for several input signal intensities. Furthermore, the maximum conversion efficiencies directly vary with input signal intensity.

Tunable filter-based multispectral imaging for detection of blood stains on construction material substrates part 2: realization of rapid blood stain detection.

Based on the blood stain detection method and criteria established in part 1 of this article, we combine and organize all necessary tasks to realize the multispectral imaging-based rapid blood stain detection system. To rapidly detect blood stains on the test surface, the developed system automatically captures the spectral images, extracts their spectral data, determines the positions of blood stains, and accurately highlights the positions of blood stains on the display. To achieve such a system, several tasks are newly introduced, including adjustment of camera exposure times to prevent image saturation or excessive darkness, the search for the sampled clean positions of the substrate to determine the substrate reflectance spectrum, and suitable detection procedures and proper arrangement of criteria to eliminate unnecessary calculations. Parallel processes between image capturing and blood stain identification help shorten the time for blood stain identifications despite a large amount of spectral data to be processed. The developed system can identify blood against several other reddish brown stains on several substrates. The measured average identification times on different test surfaces range from only 23.3 to 28.7 s, including the image capturing process.

Tunable filter-based multispectral imaging for detection of blood stains on construction material substrates. Part 1. Developing blood stain discrimination criteria.

In this article, we establish blood stain detection criteria that are less substrate dependent for use in a liquid crystal tunable filter-based multispectral-imaging system. Kubelka-Munk (KM) theory is applied to transform the acquired stains' reflectance spectra into the less substrate dependent spectra. Chosen spectral parameters are extracted from the KM absorbance spectra of several stain samples on several substrates. Blood discrimination criteria based upon those spectral parameters are then established from empirical data, tested, and refined. In our newly invented method, instead of introducing conventional contrast enhancement on the blood stain image, blood stain determination is executed mathematically via Boolean logic, resulting in more discriminative blood stain identification. This proposed approach allows for nondestructive, quick, discriminative, and easy-to-improve presumptive blood stain detection. Experimental results confirm that our blood stain discrimination criteria can be used to locate blood stains on several construction materials with high precision. True positive rates (sensitivity) from 0.60 to 0.95 are achieved depending on blood stain faintness and substrate types. Also, true negative rates (specificity) between 0.55 and 0.96 and identification time of 4-5 min are accomplished, respectively. The established blood stain discrimination criteria will be incorporated in a real blood stain detection system in part 2 of this article, where system design and considerations as well as speed issues are discussed.

Demonstration of a single-wavelength spectral-imaging-based Thai jasmine rice identification.

A single-wavelength spectral-imaging-based Thai jasmine rice breed identification is demonstrated. Our nondestructive identification approach relies on a combination of fluorescent imaging and simple image processing techniques. Especially, we apply simple image thresholding, blob filtering, and image subtracting processes to either a 545 or a 575 nm image in order to identify our desired Thai jasmine rice breed from others. Other key advantages include no waste product and fast identification time. In our demonstration, UVC light is used as our exciting light, a liquid crystal tunable optical filter is used as our wavelength seclector, and a digital camera with 640 active pixels × 480 active pixels is used to capture the desired spectral image. Eight Thai rice breeds having similar size and shape are tested. Our experimental proof of concept shows that by suitably applying image thresholding, blob filtering, and image subtracting processes to the selected fluorescent image, the Thai jasmine rice breed can be identified with measured false acceptance rates of <22.9% and <25.7% for spectral images at 545 and 575 nm wavelengths, respectively. A measured fast identification time is 25 ms, showing high potential for real-time applications.