Lambertian Reflectance Estimation for Atmospheric Correction
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Solution Overview
Problem
Existing methods for atmospheric correction of reflective band imagery require user interaction and a priori knowledge, making them cumbersome and unrealistic, especially when dealing with atmospheric effects and background reflectance mixing.
Innovation Solution
A system that estimates Lambertian equivalent reflectance using a dark pixel-based technique, automatically characterizing the atmosphere and accounting for background reflectance without user input, by solving for aerosol optical depth and background reflectance using available weather data and physics-based models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional atmospheric correction techniques are used, then atmospheric effects can be removed, but user interaction and a-priori knowledge are required
Solution Approach 1:
The system automatically identifies dark pixels and performs atmospheric correction without user interaction. The algorithm self-calibrates by detecting dark pixels in the imagery and using them to derive atmospheric parameters, eliminating the need for manual input or a-priori knowledge from users.
Solution Approach 2:
Dark pixels serve as an intermediary element that bridges the gap between raw imagery and atmospheric correction. These pixels act as natural reference targets that enable the algorithm to derive atmospheric parameters without requiring external user input or additional calibration data.
2Device complexity
If atmospheric correction is performed without accounting for background reflectance, then processing is simpler, but accuracy of surface reflectance estimation deteriorates
Solution Approach 1:
The correction process is segmented into distinct components: first deriving atmospheric parameters from dark pixels, then separately estimating background reflectance, and finally combining these corrections. This segmentation allows the complex task of accounting for background effects to be broken down into manageable steps that can be applied systematically.
Solution Approach 2:
The system performs preliminary estimation of background reflectance across the entire scene before applying pixel-level corrections. This preliminary action establishes a baseline that accounts for spatially varying background effects, enabling more accurate individual pixel corrections to follow.
3Extent of automation
If dark pixel-based technique is used, then automation is achieved, but requirement for dark pixels in scene is introduced
Solution Approach 1:
The method extracts atmospheric information directly from the imagery itself by identifying and utilizing dark pixels present in the scene. Rather than requiring external calibration data or assumptions, the system takes out the necessary correction parameters directly from the observed data, enabling automation while maintaining adaptability to different scene types that contain dark pixels.
Data Source
AI summary
A system for estimating a Lambertian equivalent reflectance for reflective band imagery is disclosed. In some embodiments, the system estimates an equivalent reflectance and performs atmospheric correction of reflective band imagery without user interaction and accounts for the effect of background reflectance mixing with individual target reflectances. Some of these embodiments use a dark pixel-based technique to improve the characterization of the atmosphere.