LocalHistogramEqualization can improve the contrast of low contrast regions of a nonlinear image. Use LocalHistogramEqualization late in the workflow when your image is nonlinear.
The process offers a real-time preview so you can get immediate feedback about how your settings affect the image.
LocalHistogramEqualization works by evaluating the pixels in a certain region and using its algorithm, enhances contrast using your settings.
Understanding LocalHistogramEqualization Parameters
The Kernel Radius setting is the number of pixels surrounding a given pixel for evaluating the histogram. Lower values increase contrast but may affect noise.
The Contrast Limit affects the transfer function with a value of 1.0 leaving the image unchanged. Adjust this parameter once you are within range of an appropriate change when adjusting the Kernel Radius.
The Amount blends the modified image with the original image. A value of 1.0 replaces the original image with the modified image and lower values blend a percentage of pixels based on the setting.
The Histogram Resolution parameter affects the bit depth of the histogram when performing the calculation and the default setting is suitable for most images. Use higher values if you see artifacts in your image.
Use the Real-Time preview to make adjustments to the parameters.
Using LocalHistogramEqualization
Start by creating a mask that protects background sky and bright stars. If you are using the AutoIntegrate-based process, you can use the L_HT image as your mask.
Alternately, you can create a mask by using a RangeMask, adjusting the lower limit to highlight your high signal areas, and then by increasing the Smoothness parameter to hide the bright stars.
Another way of creating a mask is to use the StarNet process to create a starless version of your image and then use that as the mask for LocalHistogramEqualization.
Once the mask is in place, enable the real-time preview and adjust the Kernel Radius to somewhere between 50 and 100. Then adjust the Contrast Limit between 1.5 and 3.0 once you are within the range. Adjust the Amount to somewhere between 0.25 and 0.75.
Conclusion
In this article, you learned about LocalHistogramEqualization and learned how to use it.
More Articles In This Series
This article is part of a whole series of articles about processing images using PixInsight:
- If you are using the LRGB/broadband processing workflow, click here for the index article for processing broadband images.
- If you are using the narrowband processing workflow, click here for the index article for narrowband images.
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