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Objectives: High resolution satellite images (HRSI) can provide spectral characteristics observation information of ground objects at low cost and high frequency, while light detection and ranging(LiDAR) point clouds can provide fine geometric structure. The fusion of two kinds of data can realize complementary advantages, and further improve the accuracy and automation of ground object classification and information extraction. The realization of geometric registration with sub-pixel accuracy is the premise of two kinds of data fusion. Methods: A fast registration method based on line element distance transformation model is proposed. The point clouds are used as the control source, and the typical line elements such as building edges in the point clouds are projected into the image space through the initial rational polynomial coefficient (RPC) parameters of the satellite image, and the iterative closest point registration is carried out with the line elements in the satellite image, so as to achieve geometric registration by means of refining RPC parameters. In this method, the distance transformation model is used as the search table of the iterative closest point, which greatly improves the operation efficiency. Furthermore, the latest progressive robust solution strategy is adopted at the same time of the closest point iteration, so as to ensure the robustness of registration in the case of too much noise. Registration experiments are carried out on GeoEye-2 data, Gaofen-7 data,WorldView-3 data with LiDAR point clouds data. Results: The results prove that the proposed method can achieve a registration accuracy of 0.4—0.7 m on three kinds of images by using the ground control points which are accurately measured and the operator's internal control points as checkpoints. Conclusions: It is significantly better than the strategy of mapping point clouds to 2D image and registering through multimode matching. [ABSTRACT FROM AUTHOR]

Alteration of synaptic function in the dorsal horn (DH) has been implicated as a cellular substrate for the development of neuropathic pain, but certain details remain unclear. In particular, the lack of information on the types of synapses that undergo functional changes hinders the understanding of disease pathogenesis from a synaptic plasticity perspective. Here, we addressed this issue by using optogenetic and retrograde tracing ex vivo to selectively stimulate first-order nociceptors expressing Nav1.8 (NRs Nav1.8 ) and record the responses of spinothalamic tract neurons in spinal lamina I (L1-STTNs). We found that spared nerve injury (SNI) increased excitatory postsynaptic currents (EPSCs) in L1-STTNs evoked by photostimulation of NRs Nav1.8 (referred to as Nav1.8-STTN EPSCs). This effect was accompanied by a significant change in the failure rate and paired-pulse ratio of synaptic transmission from NRs Nav1.8 to L1-STTN and in the frequency (not amplitude) of spontaneous EPSCs recorded in L1-STTNs. However, no change was observed in the ratio of AMPA to NMDA receptor-mediated components of Nav1.8-STTN EPSCs or in the amplitude of unitary EPSCs constituting Nav1.8-STTN EPSCs recorded with extracellular Ca 2+ replaced by Sr 2+ In addition, there was a small increase (approximately 10%) in the number of L1-STTNs showing immunoreactivity for phosphorylated extracellular signal-regulated kinases in mice after SNI compared with sham. Similarly, only a small percentage of L1-STTNs showed a lower action potential threshold after SNI. In conclusion, our results show that SNI induces presynaptic modulation at NR Nav1.8 (consisting of both peptidergic and nonpeptidergic nociceptors) synapses on L1-STTNs forming the lateral spinothalamic tract., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Hung et al.)