Inelastic hyperspectral Scheimpflug lidar for microalgae classification and quantification

High-Resolution Thermometric Scheimpflug LiDAR for Surface Morphology and Temperature Mapping

Common surface temperature measurement techniques, when applied to monitoring the temperature of surfaces with complex morphology, suffer from reduced spatial resolution, which compromises the measurement accuracy of the system. To improve the spatial resolution of temperature measurement technology and maintain high temperature sensitivity, we designed a microscopic morphology thermometric LiDAR (MMTL) system based on the Scheimpflug principle, which realizes the real-time restoration of the 3D morphology and temperature of the surface of micro-structured objects. The 3D spatial resolution of the system is better than 3 μm. The theoretical resolution of the self-designed reflective spectrometer can reach 0.9 nm, which improves the sensitivity and accuracy of the upconversion hybrid nanomaterials thermometry based on the intensity ratio. In the wide temperature range of 373.15-508.15 K, the highest relative temperature sensitivity can reach 2.07%/K, the optimal temperature resolution is 0.0131 K, and the error is less than 1 K. Finally, the temperature change trend of the mold surface under different heating voltages is accurately restored. The MMTL system can provide accurate temperature distribution data and hotspot location identification for scenarios such as optimizing thermal management design and real-time risk monitoring, and it has application potential in industrial manufacturing and for electronic products.

4D hyperspectral surface topography measurement system based on the Scheimpflug principle and hyperspectral imaging

A four-dimensional (4D) hyperspectral surface topography measurement (HSTM) system that can acquire uniform inelastic signals [three-dimensional (3D) spatial data] and reflection/fluorescence spectra of an object is proposed. The key components of the system are a light-sheet profilometer based on the Scheimpflug principle and a hyperspectral imager. Based on the mapping relationships among the image coordinate systems of the two imaging subsystems and the coordinate system of the real space, the spectral data can be assigned to the corresponding 3D point cloud, forming a 4D model. The spectral resolution is better than 4 nm. 700 nm, 546 nm, and 436 nm are selected as the three primary colors of red, green, and blue to restore the color. The 4D hyperspectral surface reconstruction experiments of philodendron and chlorophytum have shown the good performance of the proposed HSTM system and the great application potential for plant phenotype and growth analysis in agriculture.

Line laser scanning microscopy based on the Scheimpflug principle for high-resolution topography restoration and quantitative measurement

A line laser scanning microscopy system with a larger depth of field based on the Scheimpflug principle is proposed for high-resolution surface topography restoration and quantitative measurement on miniature non-transparent samples. An imaging model based on the Scheimpflug principle is established, and a calibration method without system parameters is derived, which is further extended to a microscopic system. The measuring range of the system is 5m m×4m m×x m m, where x is the movement distance of the displacement stage. In the z-axis direction, the relative error of measurement is about 1% when z is of the millimeter level and less than 7% when z is of the micron level, and the spatial resolution is better than 3.8 µm. In the y-axis direction, the relative error of measurement is less than 5%. Finally, three-dimensional scanning of two samples with different surfaces is carried out to verify the feasibility of the system. The experimental results show that our system has the capability of high-resolution topography restoration and can be applied in industrial production scenarios such as automatic measurement and intelligent identification.

Confocal LiDAR for remote high-resolution imaging of auto-fluorescence in aquatic media

Spatially resolved in situ monitoring of plankton can provide insights on the impacts of climate change on aquatic ecosystems due to their vital role in the biological carbon pump. However, high-resolution underwater imaging is technically complex and restricted to small close-range volumes with current techniques. Here, we report a novel inelastic scanning confocal light detection and ranging (LiDAR) system for remote underwater volumetric imaging of fluorescent objects. A continuous wave excitation beam is combined with a pinhole in a conjugated detection plane to reject out-of-focus scattering and accomplish near-diffraction limited probe volumes. The combination of bi-directional scanning with remote focusing enables the acquisition of three-dimensional data. We experimentally determine the point spread and axial weighting functions, and demonstrate selective volumetric imaging of obstructed layers through spatial filtering. Finally, we spatially resolve in vivo autofluorescence from sub-millimeter Acocyclops royi copepods to demonstrate the applicability of our novel instrument in non-intrusive morphological and spectroscopic studies of aquatic fauna. The proposed system constitutes a unique tool e.g. for profiling chlorophyll distributions and for quantitative studies of zooplankton with reduced interference from intervening scatterers in the water column that degrade the the performance of conventional imaging systems currently in place.