Hyperspectral Image Illumination Spectrum Correction via Weather Data
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Solution Overview
Problem
Existing image processing methods fail to accurately calculate and correct the illumination spectrum under varying weather conditions, such as cloudy or shaded environments, which affects the stability of captured color information in hyperspectral images.
Innovation Solution
An image processing method that estimates the illumination spectrum by calculating direct and scatter components based on insolation conditions and weather information, allowing for the conversion of images captured under arbitrary date, time, place, and weather into images as if captured under a specified illumination spectrum.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If color temperature estimation methods are used to correct illumination spectrum, then correction is effective for color images, but correction accuracy deteriorates for hyperspectral images due to large error between estimated and actual illumination spectrum
Solution Approach 1:
The invention changes the approach from estimating a single color temperature parameter to estimating multiple parameters including color temperature and tint. This multi-parameter estimation approach better captures the complexity of illumination spectra in hyperspectral images, resolving the contradiction between correction effectiveness and spectrum accuracy by using more comprehensive parameters rather than relying solely on color temperature.
2Stability of the object's composition
If illumination spectrum correction is applied to hyperspectral images, then color information stability improves, but correction accuracy deteriorates under varying weather conditions such as cloudy or shaded environments
Solution Approach 1:
The invention introduces dynamic adaptation by detecting weather conditions and selectively applying different correction strategies. Under clear sky conditions, the full illumination spectrum correction is applied, while under cloudy or shaded conditions, the correction is adjusted or bypassed. This dynamic approach maintains color information stability across varying weather conditions while preserving correction accuracy by adapting to the actual imaging environment.
3Measurement precision
If weather information is incorporated into illumination spectrum estimation, then correction accuracy improves under varying weather conditions, but system complexity increases
Solution Approach 1:
The invention uses weather information as an intermediary to bridge the gap between imaging conditions and illumination spectrum estimation. Rather than directly measuring complex atmospheric parameters, the system uses readily available weather data (clear sky, cloudy, shaded conditions) as a mediator to select appropriate correction strategies. This approach improves estimation accuracy under varying weather conditions while avoiding the complexity of direct atmospheric measurement systems.
Data Source
AI summary
The present invention relates to an illumination spectrum estimation method in which an illumination spectrum is calculated on the basis of weather information.