A Hardware-Algorithm Co-Designed Framework for HDR Imaging and Dehazing in Extreme Rocket Launch Environments
This addresses the specific problem of reliable image acquisition for quantitative mechanical analysis in extreme aerospace environments, representing a domain-specific incremental improvement.
The paper tackles the problem of quantitative optical measurement in extreme rocket launch environments where intense combustion creates dense haze and extreme luminance variations exceeding 120 dB, degrading image data. Their hardware-algorithm co-design framework combining a custom Spatially Varying Exposure sensor with a physics-aware dehazing algorithm demonstrates superior performance in recovering physically accurate visual information for extracting key mechanical parameters like particle velocity and flow instability frequency.
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 effectively separate haze from scene radiance. Validated on real launch imagery and controlled experiments, the framework demonstrates superior performance in recovering physically accurate visual information of the plume and engine region. This offers a reliable image basis for extracting key mechanical parameters, including particle velocity, flow instability frequency, and structural vibration, thereby supporting precise quantitative analysis in extreme aerospace environments.