Method for acquiring infrared images on different weather conditions

Abstract

Disclosed is a method for acquiring infrared images on different weather conditions. The method comprises steps of: S1, acquiring an aerially photographed infrared image on a first weather condition and determining an infrared radiation brightness value L1 corresponding to each pixel in the aerially photographed infrared image; S2, computing the radiation brightness of a single land feature background on the aerial photography height according to a MODTRAN simulation module, including the radiation brightness M1 on the first weather condition and the radiation brightness M2 on a second weather condition; S3, generating the conversion coefficients R of the infrared image on different weather conditions according to the M1 and the M2; and S4, computing the an infrared radiation brightness value L2 corresponding to each pixel in the infrared image on the second weather condition according to the L1 and the R. The method prevents classified identification of different land feature types and calculation errors due to uncertainty of surface reflectance and temperature, and increases computing speed.

Description

technical field [0001] The invention relates to the field of target and environment simulation, in particular to a method for acquiring infrared images under different weather conditions. Background technique [0002] In order to realistically display the infrared images of the ground object background obtained from the air, the infrared camera mounted on the aircraft is often used to shoot from the air. In the infrared image of the ground object background, the brightness signal of the image contains the comprehensive effect of the ground object and atmospheric radiation, which can be expressed as L=L atm +L scat +t L earth +tL ρ . Among them, t is the atmospheric transmittance, L atm represents the self-radiation of the atmosphere, L scat Represents the scattered radiation of atmospheric gas molecules and aerosol particles, L earth represents the ground heat radiation, L ρ Represents ground-reflected radiation. According to the source of radiation, we can put L a...

AI Technical Summary

Problems solved by technology

However, it is difficult to implement this method in some cases

For example, for areas where personnel and equipment cannot reach, it will be difficult to measure surface parameters through instruments

However, the inversion algorithm is not uniform and the inversion accuracy is uncertain

In addition, since it is necessary to identify and segment various ground object backgrounds on the real ground object background infrared image before inversion, the calculation amount and difficulty of this method are increased, and the calculation error is increased.

Images