A Hardware-Algorithm Co-Designed Framework for HDR Imaging and Dehazing in Extreme Rocket Launch Environments
Jing Tao, Banglei Guan, Pengju Sun, Taihang Lei, Yang Shang, Qifeng Yu

TL;DR
This paper introduces a hardware-algorithm co-designed system combining a custom multi-exposure sensor and physics-aware dehazing algorithms to improve optical measurements during rocket launches with extreme imaging conditions.
Contribution
It presents a novel integrated framework that jointly optimizes hardware and algorithms for effective haze removal and image enhancement in extreme aerospace environments.
Findings
Superior haze removal and image clarity demonstrated on real launch images.
Accurate extraction of mechanical parameters from enhanced images.
Robust performance under high luminance and particulate haze conditions.
Abstract
Quantitative optical measurement of critical mechanical parameters -- such as plume flow fields, shock wave structures, and nozzle oscillations -- during rocket launch faces severe challenges due to extreme imaging conditions. Intense combustion creates dense particulate haze and luminance variations exceeding 120 dB, degrading image data and undermining subsequent photogrammetric and velocimetric analyses. To address these issues, we propose a hardware-algorithm co-design framework that combines a custom Spatially Varying Exposure (SVE) sensor with a physics-aware dehazing algorithm. The SVE sensor acquires multi-exposure data in a single shot, enabling robust haze assessment without relying on idealized atmospheric models. Our approach dynamically estimates haze density, performs region-adaptive illumination optimization, and applies multi-scale entropy-constrained fusion to…
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Taxonomy
TopicsRadiative Heat Transfer Studies · Combustion and flame dynamics · Fire dynamics and safety research
