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This was a very technically difficult image to create. The reason I had to write my own software to process these images is that there is no software in existence that can properly process them, so if you want the best quality then you have to DIY your own code. The challenge in editing these pictures is three-pronged: you need to be able to align, combine, and sharpen the images.
Aligning: In images of the total solar eclipse, you must align on the wisps coming from the corona. Most people (and software) will attempt to align their images on the moon, however, the moon moves significantly during the eclipse, and is not suitable for a reference. For this reason, I used the technique of phase correlation registration, which functions off of the shift theorem of the Fourier transform. But there is a bigger problem, the contrast of the corona is way too subtle to just dump in the raw images and align them, they have to be significantly filtered to show only the highest frequency details. The edge of the moon and the edge of the image also has to be hidden.
Combining: No camera has good enough dynamic range to catch the whole eclipse in one image, you need to blend images by HDR. Most HDR software cannot handle the extreme brightness change, and they also do not preserve the faintest detail in the image. So you have to be able to combine them with a weighted sum. The weighted sum puts a preference on pixels that are properly exposed and hides pixels that are over or underexposed. The frames must be combined so that the moon is sharply composed in the image (since once again it moves too much), this is done with a complicated masking procedure.
Sharpening: Typical applications of image sharpening do not work well for images of the eclipse, because of the sharp discontinuity between the moon and the corona. The usual photoshop method of sharpening does not respect detail in all directions, it will only enhance details angularly about the center of the sun. So for this, I wrote a code to perform adaptive convolution with a variable kernel, which sharpens in all directions and avoids sharpening parts of the image where the brightness difference is too great. The variable kernel will sharpen the image in every direction where there is a large amount of signal close to the sun, but it will only sharpen angularly far away from the sun since there are no radial details in this part of the image.
All of this was coded in MATLAB. The image data was graciously provided to me by Andrew Klinger, who observed the eclipse from Missouri. I observed the eclipse from Wyoming, however, I did not have as much quality data to edit.
I hope you enjoy the image 🙂