New-Generation Fully Automatic Haze Removal and Image Clarification for Optical Satellite Imagery
AICOOL makes satellite imagery clearer, more accurate, and more reliable.
AICOOL Technology Overview
AICOOL decomposes the electromagnetic transmission equation into three components — I(X): satellite observation, J(X): true surface radiance, and H(X): haze radiance — providing a clear physical foundation for haze removal and image clarification.
Using multiscale spatial analysis, fractal and other modern mathematical methods, AICOOL automatically identifies the spatial structure of haze and separates the haze layer from the original image.
With AI-driven, fully automatic quality control, the system restores surface radiance without any parameter input, producing high-precision, haze-free images for quantitative remote sensing, land-cover analysis, and large-area monitoring.
AICOOL supports rapid, batch-mode processing for optical sensors, including satellite, aerial, and drone platforms, offering a fast and reliable solution for complex and non-uniform haze conditions.
AICOOL Key Features
- Physically based haze decomposition — Separates I(X) into J(X) and H(X) using the electromagnetic transmission equation.
- Fractal-guided haze structure detection — Identifies non-uniform haze using multiscale spatial and fractal analysis.
- Zero-parameter, fully automatic processing — No meteorological data, no atmospheric parameters, no manual tuning.
- AI-driven quality control — Automatically selects the optimal haze-removal solution.
- High-throughput batch processing — Maintains spectral fidelity across large-scale datasets.
- Multi-sensor compatibility — Works with all high-resolution optical satellite, aerial, and drone imagery.
- Haze distribution retrieval — Outputs haze intensity map H(X) for environmental applications.
- Robust under complex conditions — Effective for heavy, non-uniform, or spatially variable haze.
Why AICOOL Is Different
Traditional atmospheric correction software requires many input parameters, expert tuning, and subjective adjustments. AICOOL eliminates these limitations by directly estimating and removing the haze layer using modern mathematical tools and automated AI quality control — achieving true, high-accuracy, fully automatic haze removal.
AICOOL vs ATCOR
ATCOR uses physical atmospheric modeling and requires parameter inputs such as visibility, aerosol type, and water vapor.
AICOOL requires no inputs, uses spatial–fractal analysis to extract haze directly from the image, and includes automatic AI evaluation for clarity optimization.
Example Visual Results
Application Areas
- Land cover / land use monitoring
- Urban change detection
- Biodiversity monitoring
- Environmental management
- Crop analysis and precision agriculture
- Disaster response mapping