Use of high dynamic range imaging for quantitative combustion diagnostics

Abstract

High dynamic range (HDR) imaging is applied to quantitative combustion diagnostics in coflow laminar diffusion flames as a way to improve the signal-to-noise ratio (SNR) and measurement sensitivity. The technique relies on the combination of partially saturated frames into a single unsaturated image; in this work, the effectiveness of the HDR approach is demonstrated when applied to two-color ratio pyrometry. Specifically, it is shown than an increase in SNR results in more precise temperature measurements for both soot and thin filament pyrometry. Linearity and reciprocity analysis under partially saturated conditions were performed on three selected detectors, and the camera response functions, which are required for HDR image reconstruction, were determined. The linearity/reciprocity of the detectors allowed the use of a simplified algorithm that was implemented to compute the HDR images; soot and flame temperature were calculated from those images by employing color-ratio pyrometry. The reciprocity analysis revealed that pixel cross talk can be a limiting factor in a detector's HDR capabilities. The comparison with low dynamic range results showed the advantage of the HDR approach. Due to the higher SNR, the measured temperature exhibits a smoother distribution, and the range is extended to lower temperature regions, where the pyrometry technique starts to lose sensitivity due to detector limitations.

High dynamic spectroscopy using a digital micromirror device and periodic shadowing

“…A dynamic range higher than the capacity offered by a given camera system can be achieved using a concept based on multiple exposures [12,14]. In this concept, often referred to as High Dynamic Range (HDR), each exposure time is made different; one short to capture intense regions, one long wherein dimmer regions become visible and then one or several at intermediate times.…”

High Dynamic Range Fluorescence Imaging

“…In these techniques, images with varying degrees of saturation are fused together to give rise to a single unsaturated image covering a dynamic range larger than the one of the single acquired images. Lately this strategy has also been extended into the biological, biomedical and clinical fields [5] as well as other imaging areas [6–8]. High dynamic range (HDR) X-ray radiographic imaging experiments have been shown to accurately resolve the internal features of complicated structural components at different thicknesses [9].…”

Improved Threat Identification Using Tonemapping of High-Dynamic-Range X-ray Images

“…There has been much research into HDR techniques beyond conventional visible light photography. The breadth of this work will not be surveyed here, but we point the interested reader to examples where HDR processing techniques have also been advantageously applied to sonar [9], radar [10], and audio processing [11,12]. At X-ray wavelengths, Park and Montag investigated the performance of nine tonemapping algorithms for rendering scientific HDR images, including medical radiographs [13].…”