Research on the Improvement of Semi-Global Matching Algorithm for Binocular Vision Based on Lunar Surface Environment.

The low light conditions, abundant dust, and rocky terrain on the lunar surface pose challenges for scientific research. To effectively perceive the surrounding environment, lunar rovers are equipped with binocular cameras. In this paper, with the aim of accurately detect obstacles on the lunar surface under complex conditions, an Improved Semi-Global Matching (I-SGM) algorithm for the binocular cameras is proposed. The proposed method first carries out a cost calculation based on the improved Census transform and an adaptive window based on a connected component. Then, cost aggregation is performed using cross-based cost aggregation in the AD-Census algorithm and the initial disparity of the image is calculated via the Winner-Takes-All (WTA) strategy. Finally, disparity optimization is performed using left-right consistency detection and disparity padding. Utilizing standard test image pairs provided by the Middleburry website, the results of the test reveal that the algorithm can effectively improve the matching accuracy of the SGM algorithm, while reducing the running time of the program and enhancing noise immunity. Furthermore, when applying the I-SGM algorithm to the simulated lunar environment, the results show that the I-SGM algorithm is applicable in dim conditions on the lunar surface and can better help a lunar rover to detect obstacles during its travel.

Improvement of AD-Census Algorithm Based on Stereo Vision.

Problems such as low light, similar background colors, and noisy image acquisition often occur when collecting images of lunar surface obstacles. Given these problems, this study focuses on the AD-Census algorithm. In the original Census algorithm, in the bit string calculated with the central pixel point, the bit string will be affected by the noise that the central point is subjected to. The effect of noise results in errors and mismatching. We introduce an improved algorithm to calculate the average window pixel for solving the problem of being susceptible to the central pixel value and improve the accuracy of the algorithm. Experiments have proven that the object contour in the grayscale map of disparity obtained by the improved algorithm is more apparent, and the edge part of the image is significantly improved, which is more in line with the real scene. In addition, because the traditional Census algorithm matches the window size in a fixed rectangle, it is difficult to obtain a suitable window in the image range of different textures, affecting the timeliness of the algorithm. An improvement idea of area growth adaptive window matching is proposed. The improved Census algorithm is applied to the AD-Census algorithm. The results show that the improved AD-Census algorithm has been shown to have an average run time of 5.3% and better matching compared to the traditional AD-Census algorithm for all tested image sets. Finally, the improved algorithm is applied to the simulation environment, and the experimental results show that the obstacles in the image can be effectively detected. The improved algorithm has important practical application value and is important to improve the feasibility and reliability of obstacle detection in lunar exploration projects.

Nitric oxide detection using catalytic properties of CuCo-PTC metal organic framework.

As a vital gaseous signal molecule involved in various physiological and pathological processes, nitric oxide (NO) has attracted extensive attention in the last few decades. In this work, a copper and cobalt element-doped, biphenyl-(3, 4', 5)-tricarboxylic acid (H3PTC)-synthesized metal organic framework (CuCo-PTC MOF) composite with catalytic ability was synthesized by solvothermal method. The material can catalyse the oxidation of o-phenylenediamine (OPD) groups by hydrogen peroxide (H2O2) to form fluorophores (OPDox) with yellow fluorescence emission and greatly improves its reaction rate. In the presence of NO, OPD will react with NO to produce N-(2-hydrazinophenyl) methylamine, and the group will not react with H2O2. Therefore, the concentration of NO can be measured indirectly by comparing the changes of fluorescence intensity in the presence and absence of NO. As the concentration of NO changes, the change of solution colour (from bright yellow to colourless) can also be observed under a 365-nm UV lamp. Furthermore, the method represents high selectivity for NO and shows a fast (within 5 min) and specific fluorescence response toward NO with a linear range from 0.25 to 2.0 µM; the strategy has a limit of detection (LOD) of  0.15 µM. More importantly, the probe was successfully used to detect NO in cell lysate. The recovery was between 98.5 and 103.6%, and the relative standard deviation was between 0.4 and 1.8%. The endogenous NO in cells was successfully detected under the stimulation of L-arginine, which proved the possibility of the probe in real-time and rapid sensing in actual samples and cells. The results indicate that this sensing strategy has the potential to detect NO in the internal environment. Schematic of fluorescence detection of NO.