Assessment of DSM Based on Radiometric Transformation of UAV Data

A Study on the Determination Methods of Monitoring Point for Inundation Damage in Urban Area Using UAV and Hydrological Modeling

Recently, unmanned aerial vehicles (UAVs) have been used in various fields, such as military, logistics, transportation, construction, and agriculture, making it possible to apply the limited activities of humans to various and wide ranges. In addition, UAVs have been utilized to construct topographic data that are more precise than existing satellite images or cadastral maps. In this study, a monitoring point for preventing flood damage in an urban area was selected using a UAV. In addition, the topographic data were constructed using a UAV, and the flow of rainwater was examined using the watershed analysis in an urban area. An orthomosaic, a digital surface model (DSM), and a three-dimensional (3D) model were constructed for the topographic data, and a precision of 0.051 m based on the root mean square error (RMSE) was achieved through the observation of ground control points (GCPs). On the other hand, for the watershed analysis in the urban area, the point in which the flow of rainwater converged was analyzed by adjusting the thresholds. A monitoring point for preventing flood damage was proposed by examining the topographic characteristics of the target area related to the inflow of rainwater.

Intelligent Enhancement Algorithm-Based High Resolution CT Image in Evaluation of Expelling Wind and Relieving Cough and Asthma Prescription on Bronchial Asthma with High Immunoglobulin E Expression

The therapeutic effect of expelling wind and relieving cough and asthma prescription on bronchial asthma with high immunoglobulin E (IgE) expression was studied based on high resolution CT (HRCT) images of intelligent enhancement algorithm. 90 patients with bronchial asthma were randomly divided into control group ( $n=45$ ) and therapy group ( $n=45$ ). The control group was given budesonide inhalation. The therapy group was treated with expelling wind and relieving cough and asthma prescription on the basis of the treatment in the control group. Both groups were given 1 month of treatment time. The scanned images were processed by image enhancement algorithm, and the image quality and distribution separation measurement (DSM) were used as image evaluation indicators. The bronchial wall thickness (WT), inner diameter (L), wall area (WA), and percentage of wall area (WA%) were used as quantitative indicators of airway remodeling. The changes of traditional Chinese medicine (TCM) score before and after treatment were recorded and analyzed. The changes of serum IgE indicators before and after treatment were recorded. Results: the image quality of HRCT image enhancement algorithm was better, and the DSM was 36.7 larger than that of the control group. It was found that after 1 month of treatment, the TCM symptom score of the therapy group was lower than that of the control group ( $P<0.05$ ), and compared with the control group, the IgE level of the therapy group was also reduced. Meanwhile, compared with the control group, the WT of segmental bronchial wall in the therapy group decreased, and the WT of left apical bronchus was smaller than that in the control group ( $P<0.05$ ), and the WT of subsegmental bronchus decreased significantly ( $P<0.05$ ). The $L$ of segmental bronchus and subsegmental bronchus in the therapy group was wider ( $P<0.05$ ). The WA of segmental bronchus and subsegmental bronchus decreased, but there was no statistical significance ( $P>0.05$ ). Compared with the control group, the WA percentage of segmental bronchus and the WA percentage of subsegmental bronchus in the therapy group were significantly lower ( $P<0.05$ ). In conclusion, image enhancement algorithm can improve the HRCT image quality of patients with bronchial asthma, which is helpful to improve the diagnostic efficiency in clinical treatment. Expelling wind and relieving cough and asthma prescription has a better therapeutic effect on bronchial asthma with high IgE expression.

Polymodal Method of Improving the Quality of Photogrammetric Images and Models

Photogrammetry using unmanned aerial vehicles has become very popular and is already commonly used. The most frequent photogrammetry products are an orthoimage, digital terrain model and a 3D object model. When executing measurement flights, it may happen that there are unsuitable lighting conditions, and the flight itself is fast and not very stable. As a result, noise and blur appear on the images, and the images themselves can have too low of a resolution to satisfy the quality requirements for a photogrammetric product. In such cases, the obtained images are useless or will significantly reduce the quality of the end-product of low-level photogrammetry. A new polymodal method of improving measurement image quality has been proposed to avoid such issues. The method discussed in this article removes degrading factors from the images and, as a consequence, improves the geometric and interpretative quality of a photogrammetric product. The author analyzed 17 various image degradation cases, developed 34 models based on degraded and recovered images, and conducted an objective analysis of the quality of the recovered images and models. As evidenced, the result was a significant improvement in the interpretative quality of the images themselves and a better geometry model.