7 results about "Sky brightness" patented technology

The invention discloses an engineering structure crack detection method and system based on an image processing technology, and relates to the technical field of image processing, and the method comprises the following steps: S100, collecting image data of a plurality of time points in an engineering structure monitoring area, obtaining a corresponding sky brightness change curve and a reflector reflection angle change sequence, and obtaining a corresponding sky brightness change curve; generating a time-varying illumination profile covering a monitoring period and a reflector trajectory map, and constructing an illumination baseline for subsequent time sequence reference; and S200, deriving a brightness fluctuation sensitivity field according to the illumination baseline, screening an area with stable brightness response in the sensitivity field as an edge anchor point set, and carrying out initial position calibration on the crack candidate boundary by using the edge anchor point set. The crack identification stability is improved through the steps of dynamic illumination modeling, brightness sensitivity analysis, radiation calibration, boundary reestimation and the like, and high-precision, self-adaptive and sustainable optimization of crack detection in a complex environment is realized by introducing a closed-loop control and self-learning mechanism.

The invention provides a multi-climate zone-oriented photovoltaic car shed assembly inclination angle adjusting method and system, and the method comprises the steps: obtaining a low-altitude topographic cumulus real-time distribution image and sky brightness data through an all-sky imager, and combining the speed and direction of valley wind collected by an anemorumbometer, generating a meteorological feature data set including a cloud body edge, a shadow boundary and a moving path; extracting a shadow coverage state of the high-altitude shed from the shadow evolution time sequence, if the high-altitude shed is not in shadow coverage, determining that a solar panel of the high-altitude shed maintains a target direct light receiving inclination angle, and generating an inclination angle maintaining instruction; the inclination angle adjusting instruction and the inclination angle maintaining instruction are distributed to solar panel control units of low-altitude and high-altitude carports, servo motors are driven to adjust panel angles, and inclination angle optimization is completed; and evaluating the data set according to the optimization effect, calculating the deviation between the photoelectric conversion efficiency and the preset expected scattered light capture efficiency, and updating the terrain constraint parameters according to the deviation.

The application discloses a FAST core array broadband beam effect elimination method based on deep learning, relates to the technical field of radio astronomy image processing, and constructs an end-to-end image restoration system, which comprises the following five steps: acquiring an observation image containing a broadband beam effect; extracting multi-scale features and introducing a spatial perception mechanism; performing feature frequency domain enhancement processing and multi-scale context fusion; and outputting a multi-scale prediction image and a restored image from which the broadband beam effect is removed. The application realizes the function of improving imaging quality by constructing a deep learning model, avoids cumulative errors caused by step-by-step processing, can effectively remove broadband beam distortion, and makes the reconstructed image more close to the real sky brightness distribution in overall fidelity and structural details, and has higher physical consistency.

The present invention provides a dust aerosol identification method, system, model training method, medium, and equipment. The dust aerosol identification model training method includes obtaining training thermal infrared observation brightness temperature data, training simulated clear sky brightness temperature data, and training surface information data; obtaining clear sky labels, cloud labels, and dust labels corresponding to the training thermal infrared observation brightness temperature data, the training simulated clear sky brightness temperature data, and the training surface information data; and training the dust aerosol identification model based on the training thermal infrared observation brightness temperature data, the training simulated clear sky brightness temperature data, the training surface information data, and the clear sky labels, cloud labels, and dust labels. The present invention can eliminate the influence of clouds and the surface, accurately identify thin dust aerosols in all weather conditions, and does not require an additional cloud detection program as preprocessing, thereby reducing the steps in the dust identification process, improving the accuracy of dust identification, and effectively achieving the distinction between clear sky, clouds, and dust.

A kind of road marking brightness measurement method based on the imaging principle of digital camera belongs to the field of road engineering.The present application measures the brightness of road marking by using the imaging principle of digital camera, thereby replacing the existing road marking brightness measurement method to measure the service performance of road marking.Digital camera test can not only realize the regional measurement of road marking brightness, but also reduce the influence degree of sky brightness on road marking brightness test, and can effectively improve the efficiency of road marking brightness test.The present application can not only realize the accurate expression of road marking brightness, but also save the time and fund consumption of road detection, and then efficiently guarantee the safety of traffic operation, and has important economic value and social value.

The embodiment of the invention provides a runway visual range deviation evaluation method based on background light brightness and light fusion. The method comprises the following steps: acquiring a brightness gradient mutation feature of a runway sidelight sequence in a continuous frame video in a V channel of an HSV color space; extracting a preliminary regulation and control parameter of a light pulse duty ratio based on the brightness gradient mutation feature; dynamically correcting the preliminary regulation and control parameters in combination with a spatial Laplace change rate of background sky brightness; and performing frame-by-frame light pulse duty ratio regulation and control according to the corrected regulation and control parameters so as to compensate perceptual drift of human eyes to flickering light fusion frequency. Through the scheme of the embodiment of the invention, the problem that visual range interpretation is lagged due to the fact that human eyes perceive drifting of flickering light fusion frequency under low visibility can be solved.

The application discloses a sky color modeling method based on sunny spectrum information, and solves the problems that existing sky brightness models cannot restore sky color information and color deviation exists when color is represented by correlated color temperature. The spectrum data of 145 sky surface elements of a hemisphere are measured by a spectrum sky scanner; color coordinates (x, y) of each sky surface element are solved based on the spectrum data; a zenith color model is established based on direct and scattered data; a BP neural network model framework is built; and the input layer is set as the sky surface element height angle, the sky surface element azimuth angle, the sun height angle, the sun azimuth angle and the zenith color coordinate value to obtain the final model. The method of the application establishes a model with color information to improve the application of the sky model in the field of colorimetry. The model is used to estimate the real-time sky spectrum data variation law, and provides a theoretical reference for building lighting simulation of glass with spectrum selectivity. The color coordinates are more scientific and accurate than the correlated color temperature.