Hemagglutination Detection with Paper–Plastic Hybrid Passive Microfluidic Chip

Hemagglutination is a critical reaction that occurs when antigens expressed on red blood cells (RBCs) react with the antibodies used for blood typing. Even though blood typing devices have been introduced to the market, they continue to face several limitations in terms of observation by the eye alone, blood manipulation difficulties, and the need for large-scale equipment, particularly process automated machines. Thus, this study aimed to design, fabricate, and test a novel hybrid passive microfluidic chip made of filter paper and polymer using a cost-effective xurography manufacturing technique. This chip is referred to as the microfluidic paper–plastic hybrid passive device (PPHD). A passive PPHD does not require external sources, such as a syringe pump. It is composed of a paper-based component that contains dried antibodies within its porous paper and a polymer component that serves as the detection zone. A single blood sample was injected into the chip’s inlet, and classification was determined using the mean intensity image. The results indicated that embedded antibodies were capable of causing RBC agglutination without a saline washing step and that the results could be classified as obviously agglutination or nonagglutination for blood typing using both the naked eye and a mean intensity image. As a proof-of-concept, this study demonstrated efficiency in quantitative hemagglutination measurement within a passive PPHD for blood typing, which could be used to simplify blood biomarker analysis.

Hue-Preserving Saturation Improvement in RGB Color Cube

This paper proposes a method for improving saturation in the context of hue-preserving color image enhancement. The proposed method handles colors in an RGB color space, which has the form of a cube, and enhances the contrast of a given image by histogram manipulation, such as histogram equalization and histogram specification, of the intensity image. Then, the color corresponding to a target intensity is determined in a hue-preserving manner, where a gamut problem should be taken into account. We first project any color onto a surface in the RGB color space, which bisects the RGB color cube, to increase the saturation without a gamut problem. Then, we adjust the intensity of the saturation-enhanced color to the target intensity given by the histogram manipulation. The experimental results demonstrate that the proposed method achieves higher saturation than that given by related methods for hue-preserving color image enhancement.

Monitoring Dynamic Evolution of the Glacial Lakes by Using Time Series of Sentinel-1A SAR Images

As an approach with great potential, the interpretation of space-borne synthetic aperture radar (SAR) images has been applied for monitoring the dynamic evolution of the glacial lakes in recent years. Considering unfavorable factors, such as inherent topography-induced effects and speckle noise in SAR images, it is challenging to accurately map and track the dynamic evolution of the glacial lakes by using multi-temporal SAR images. This paper presents an improved neighborhood-based ratio method utilizing a time series of SAR images to identify the boundaries of the glacial lakes and detect their spatiotemporal changes. The proposed method was applied to monitor the dynamic evolution of the two glacial lakes with periodic water discharge at the terminus of the Gongba Glacier in the southeastern Tibetan Plateau by utilizing 144 Sentinel-1A SAR images collected between October of 2014 and November of 2020. We first generated the reference intensity image (RII) by averaging all the SAR images collected when the water in the glacial lakes was wholly discharged, then calculated the neighborhood-based ratio between RII and each SAR intensity image, and finally identified the boundaries of the glacial lakes by a ratio threshold determined statistically. The time series of areas of the glacial lakes were estimated in this way, and the dates for water recharging and discharging were accordingly determined. The testing results showed that the water of the two glacial lakes began to be recharged in April and reached their peak in August and then remained stable dynamically until they began to shrink in October and were discharged entirely in February of the following year. We observed the expansion process with annual growth rates of 3.19% and 12.63% for these two glacial lakes, respectively, and monitored a glacial lake outburst flood event in July 2018. The validation by comparing with the results derived from Sentinel-2A/B optical images indicates that the accuracy for identifying the boundaries of the glacial lakes with Sentinel-1A SAR images can reach up to 96.49%. Generally, this contribution demonstrates the reliability and precision of SAR images to provide regular updates for the dynamic monitoring of glacial lakes.

Optimization Algorithm of Infrared-Polarization Image Fusion Based on Fireworks Algorithm

Because of the shortcomings of traditional infrared-polarization image fusion algorithm, such as low intelligence and single optimization index, this paper proposes an intelligent infrared-polarization image fusion optimization algorithm based on fireworks algorithm. Firstly, an improved differential image correction method based on single pixel nonuniformity is proposed to remove the cold reflection. The two-dimensional discrete cosine transform (DCT) is used to reduce the image sensitivity and improve the robustness, and the Stokes vector formula is used to obtain the polarization characteristic image. Secondly, based on the strong complementarity between infrared-intensity image and degree of linear-polarization (DOLP) image and the explosive optimization of fireworks algorithm, the problem model of weighted fusion algorithm is established, and the fitness function based on root mean square error (RMSE) is constructed to calculate the optimal weight of source image. In the fusion experiment of long-wave infrared-intensity image and DOLP image, this method is compared with the common fusion algorithms. The results show that this method can effectively fuse the infrared-intensity and degree of polarization information, and the evaluation indexes of standard deviation, spatial frequency, mutual information, structural similarity, peak signal-to-noise ratio and information entropy of the fusion image are better than the comparison algorithm. In the future, cooperated with the long-wave infrared-polarization imaging system, this method can be applied to improve the infrared detection ability in complex environment.