主动光照条件下水面菲涅尔反射系数的自感知与校正方法
By using modulation and differential spectral processing of artificial light sources under active illumination conditions, the water surface and light source signals are directly separated. The water surface roughness is self-sensed and weighted integraled, solving the problem of the inability to adaptively correct the Fresnel reflectance coefficient in existing technologies. This enables accurate all-weather remote sensing reflectance measurement of water bodies, reducing system complexity and maintenance costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING HYDRAULIC RES INST
- Filing Date
- 2026-05-15
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies rely on external equipment or empirical assignment to obtain the Fresnel reflectance coefficient of water surface under active lighting conditions, which cannot achieve adaptive and accurate correction, especially in unattended scenarios where the equipment is complex and maintenance costs are high.
By processing the geometric parameters and differential spectrum of the artificial light source, the geometric parameters of the light source and the differential light source are directly separated, and the interaction signal between the light source and the water surface is directly separated. The measured specular reflection intensity is obtained in real time using the near-infrared band in the differential spectrum. The water surface roughness index and wave slope variance are calculated by combining the known geometric parameters of the artificial light source with the theoretical reflection intensity, so as to realize the self-sensing of the dynamic optical characteristics of the water surface. Then, the accurate effective Fresnel reflection coefficient is obtained by weighted integration, and adaptive accurate correction is achieved under all-weather conditions.
It enables accurate measurement of water reflectance under all-weather conditions, reduces reliance on external equipment, lowers system complexity and maintenance costs, and is suitable for long-term operation in unattended scenarios.
Smart Images
Figure CN122193166B_ABST