![FlameMaster- LIF Image Processing Software](https://www.superbin.com.tw/storage/images/product/Optical-measurement-solutions/FluidMaster/Scalar-imaging-software/scalar-imaging-software.jpg)
LIF Image Processing Software
Quantitative LIF imaging relies on accurately mapping the florescence light-intensity collected by a camera into physical units, such as concentration or temperature. Towards that end, two dedicated software modules are available in LaVision DaVis: the LIF software base module (1-color) and the add-on LIF ratiometric software module (2-color). The complex workflow of quantitative scalar-imaging includes noise-filtering and masking, background, laser-sheet and flat-field corrections, and finally a calibration which converts the processed signal intensity to the desired physical unit. The new LIF Image Processing module streamlines this workflow by introducing a fully integrated processing-dialog that incorporates all required processing steps in a single operation.
![Image Pre-Processing](/storage/images/product/Optical-measurement-solutions/FluidMaster/Scalar-imaging-software/image-pre-processing.gif)
Image Pre-Processing
The accurate quantification of LIF signals requires the application of numerous processing steps prior to calibration. These are seamlessly integrated in an interactive dialog which includes:
- Geometric masking to restrict the calculation to the user’s area of interest
- Background subtraction and flat-field correction routines to account for cameras dark current, inhomogeneities, vignetting and image distortion effects
- Intensity corrections to compensate for laser energy fluctuations
- Masking filters to reject areas with low intensity and poor SNR
- Noise filtering routines using spatial (Gaussian) smoothing
![Hydrogen-injection](/storage/images/product/Optical-measurement-solutions/FluidMaster/Scalar-imaging-software/LIF-signal-calibration.gif)
LIF Signal Calibration
LIF images at specified calibration conditions must be recorded and processed in order to quantify the relationship between the photo-emission response of the tracer and the quantity of interest. The new LIF Image Processing allows the user to:
- Generate calibration curves for a wide range of scalars including pH values, dye and species concentration, soot concentration via LII and gas/liquid temperature
- Select suitable fit models
- Use pre-defined sequences for automated calibration
- Achieve sub-pixel mapping for high fidelity 2-color ratiometric LIF
![SNR Analysis](/storage/images/product/Optical-measurement-solutions/FluidMaster/Scalar-imaging-software/SNR-analysis.gif)
SNR Analysis
The final 2D map of the measured scalar contains additional signal-to-noise (SNR) and measurement-uncertainty distributions. This allows the user to:
- Quickly and intuitively gauge the fidelity of the measurement on a per-image basis and in a space-resolved manner
- Identify and isolate areas with reliable content based on locally high SNR
- Optimize pre-processing operations to boost the SNR of the measurement in conjunction with the desired spatial resolution
![Uncertainty Analysis](/storage/images/product/Optical-measurement-solutions/FluidMaster/Scalar-imaging-software/uncertainty-analysis.gif)
Uncertainty Analysis
Measurement uncertainties from photon and camera noise, and uncertainties during the calibration and data-processing are considered in the analysis:
- Independent treatment of random and systematic uncertainties
- Uncertainty quantification and propagation at each processing step
- Visualization of the individual and total uncertainties of the intermediate and final measurement results
![Interactive Live Processing](/storage/images/product/Optical-measurement-solutions/FluidMaster/Scalar-imaging-software/interactive-live-processing.jpg)
Interactive Live Processing
The LIF software features fast processing with live-preview updated at any change of the processing-parameters. Consequently, the user interface updates the result in real time, allowing the user to seamlessly experiment with the parameters of the workflow, thus facilitating the optimization of data processing.
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