Effective contrast enhancement method for color night vision

Image fusion refers to the techniques that integrate complementary information from multiple image sensors’ data in a way that makes the new images more suitable for human visual perception. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Firstly, the contrast of infrared and visible images is enhanced using local histogram equalization and median filter. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To enhance the color contrast between the target and the background, the scaling factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot and cold targets are all popped out with intense colors while the background details present natural color appearance. Target detection experiments through target recognition area, detection rate, target-background discrimination also show that the presented method has a better performance than the former methods.     

Resolution improvement for enhancing interference fringes of digital holograms with near infrared illuminance

A new resolution improving method of enhancing the interference stripes, which can achieve better reconstruction of the recorded object of infrared digital holography has been proposed in this paper. The experiment is conducted under near infrared illuminance. We create poor quality holograms with very low-resolution interference stripes and enhance it with our new method. The processed holograms have much higher-resolution interference stripes. This method is based on interpolation theory, and we make it works fast, stable and easy to apply. Both the forward and backward interpolation of the oriental and portrait direction of the source pixels have been calculated, and have been used to realize the final aim of resolution improvement. During the experiment, since the responsivity of the CCD is not satisfied with the illuminance laser, which is by design, we also give specific analysis on the experimental setup of our work to make sure the object information can be fully recorded by the optical setup but cannot be reconstructed because of the low-resolution and unobvious of the interference stripes. After the resolution improvement process of the original hologram, the object information can then be fully reconstructed, which is very clear in the paper. Figures and dataflow give evidence and demonstrate the good performance of our method.     

A simple and high‐resolution HPLC‐PDA method for simultaneous quantification of local anesthetics in in vitro buccal permeation enhancement studies

A simple, isocratic, high‐resolution and prompt HPLC‐PDA method was developed and validated for the simultaneous quantification of prilocaine (PCL) and lidocaine (LCL) hydrochlorides in in vitro buccal iontophoresis‐driven permeation studies. A reversed‐phase C₁₈ column (250 mm x 4.6 mm, 3μm, 110Å) was used for the chromatographic separation. The mobile phase contained acetonitrile: 0.1M sodium phosphate buffer, pH 7.0 (1:1, v/v), plus 0.05% (v/v) diethylamine. The isocratic flow rate was set at 1 mL/min and the detection wavelength was 203 nm. PCL and LCL eluted in 8.9 min and 13 min, respectively, and the system suitability parameters varied within an acceptable range. The method was selective, sensitive, precise, accurate and robust, producing a linear plot at the concentration range of 0.25 to 10 µg/mL. The application of this method was demonstrated by a significant enhancement of the permeation of PCL and LCL with the application of iontophoresis (1 mA/cm² per 1 h) through isolated porcine esophageal epithelium. The amount of the drug retained in the epithelium also increased with the application of an electrical current. Copyright © 2015 John Wiley & Sons, Ltd.     

Fingerprint image enhancement using data driven Directional Filter Bank

A new method based upon data driven tool, principal component analysis (PCA), for fingerprint enhancement is proposed in this paper. PCA is a very useful statistical technique that has found application in many different fields like image compression, face recognition and is commonly used for finding patterns in data of high dimension. In the proposed method, the input image is first decomposed into directional images using decimation free Directional Filter Bank (DDFB). Then these directional images are normalized. A data driven technique PCA is applied to these normalized directional fingerprint images, which gives the PCA filtered images. These are basically directional images. Then these directional images are reconstructed into one image which is the enhanced one. Simulation results are included illustrating the capability of the proposed method.     

Plasmonic nanostructures for local field enhancement in the UV region

In this work we describe an ultraviolet subwavelength focusing in plasmonic nanostructures. A system which provides a 20–25 times local field enhancement at a wavelength of 350 nm is proposed. This system represents a metalized V-shaped groove in a surface of a dielectric medium. Subwavelength focusing is achieved by a plasmon wave propagation along the surface of metal film and by the transfer of electromagnetic field through the dielectric medium. The influence of system parameters on a local field enhancement is investigated. A simplified model that allows for determining the geometric parameters of an optimized resonator is proposed.     

聚乙烯吡咯烷酮纳米银荧光增强测定番茄红素

合成了聚乙烯吡咯烷酮纳米银,研究了番茄红素对聚乙烯吡咯烷酮纳米银体系的荧光增强效应。考察了缓冲体系、纳米银用量、聚乙二醇浓度、反应时间和温度等因素的影响,建立了测定番茄红素的新方法。在最佳条件下,体系的相对荧光强度与番茄红素浓度呈良好的线性关系,其线性范围为2.0×10-6~8.0×10-5 mol/L,检出限为1.6×10-8 mol/L。方法应用于实际样品检测,回收率为98.29%~109.36%。     

Explicit–implicit mapping approach to nonlinear blind separation of sparse nonnegative dependent sources from a single mixture: pure component extraction from nonlinear mixture mass spectra

The nonlinear, nonnegative single‐mixture blind source separation problem consists of decomposing observed nonlinearly mixed multicomponent signal into nonnegative dependent component (source) signals. The problem is difficult and is a special case of the underdetermined blind source separation problem. However, it is practically relevant for the contemporary metabolic profiling of biological samples when only one sample is available for acquiring mass spectra; afterwards, the pure components are extracted. Herein, we present a method for the blind separation of nonnegative dependent sources from a single, nonlinear mixture. First, an explicit feature map is used to map a single mixture into a pseudo multi‐mixture. Second, an empirical kernel map is used for implicit mapping of a pseudo multi‐mixture into a high‐dimensional reproducible kernel Hilbert space. Under sparse probabilistic conditions that were previously imposed on sources, the single‐mixture nonlinear problem is converted into an equivalent linear, multiple‐mixture problem that consists of the original sources and their higher‐order monomials. These monomials are suppressed by robust principal component analysis and hard, soft, and trimmed thresholding. Sparseness‐constrained nonnegative matrix factorizations in reproducible kernel Hilbert space yield sets of separated components. Afterwards, separated components are annotated with the pure components from the library using the maximal correlation criterion. The proposed method is depicted with a numerical example that is related to the extraction of eight dependent components from one nonlinear mixture. The method is further demonstrated on three nonlinear chemical reactions of peptide synthesis in which 25, 19, and 28 dependent analytes are extracted from one nonlinear mixture mass spectra. The goal application of the proposed method is, in combination with other separation techniques, mass spectrometry‐based non‐targeted metabolic profiling, such as biomarker identification studies. Copyright © 2015 John Wiley & Sons, Ltd.     

Morphology-controlled electrochemical sensing amaranth at nanomolar levels using alumina

Different-shaped aluminas were readily prepared via hydrothermal reaction. It was found that the morphology and the electrochemical sensing properties of alumina were heavily dependent on the reaction time. When extending the reaction time from 6 h to 24 h, the obtained alumina samples changed from amorphous bumps to regular microfibers in diameter of 200 nm, as confirmed by scanning electron microscopy. Transmission electron microscopy observation revealed that longer reaction time was beneficial for the formation of porous and uniform fiber-like structures. Electrochemical tests proved that alumina microfibers were more active for the oxidation of amaranth and exhibited much higher enhancement effect, compared with alumina bumps. On the surface of alumina microfibers, the oxidation peak currents of amaranth increased remarkably. The influences of pH value, amount of alumina microfibers, and accumulation time on the signal enhancement of amaranth were discussed. As a result, a novel electrochemical method was developed for the detection of amaranth. The linear range was from 1 to 150 nM, and the detection limit was 0.75 nM after 1-min accumulation. The analytical application in drink samples was investigated, and the results consisted with the values that obtained by high-performance liquid chromatography.