I did not use Astra Image but here is my effort anyway. I am at home sick today so this was a nice way to pass the time, keep my mind off my pounding headache.
For the most part I used a piece of free software called
ImageJ, and the FFTJ and DeconvolutionJ plugins. I use it in Linux but it runs on just about anything (it's java based).
For best results deconvolution should be applied before any other image processing operations. So I chose a this starting image (see first attached pic): 1__ST149_WV10_10_58_91_118_186.tif, because it roughly looks like it has the degree of blurring expected for the telescope used (which will blur out of details smaller than about 4-7 pixels depending on colour), and does not show any visible signs of processing, i.e., sharpening (unlike e.g. 1__ST149_WV10_10_58_138_293_455.tif , which is a bit sharper but shows a bit of a white halo around the moon shadow).
For the deconvolution operations I estimated the point spread function (PSF) based on the following parameters:
* diameter of Jupiter on image = 412 pixels (measured with kruler off the screen, +/- 4 pixels)
* angular size of Jupiter = 40.1 arc sec (assume picture taken on 25/06/06)
=> we have pixel size = 0.09733 arc sec
* Telescope aperture = 250mm (10" Dob)
* Central obstruction = 65mm (info about 10" Dob in previous posts on IIS)
* wavelength = 475nm (blue), 510nm (green), 650nm (red)
I wrote a short C++ program to calculate the PSF with Bessel function J1 from the
GNU Scientific Library. I generated 3 PSFs, one for each colour. (See attached image - PSFs are shown at four times actual size and gamma adjusted to show ring structure.)
Decomposed the image into RGB channels and deconvoluted each using the corresponding PSF. The FFTJ plugin is a one-step direct method of deconvolution. There is a "regularisation parameter" that needs to be chosen appropiately (for best compromise between noise and sharpness). I chose these values by inspection: red: 0.002, green: 0.00005, blue: 0.001, which gave good detail plus a bit of speckle noise.
Then:
- RGB merge
- Despeckle: ImageJ has a very good parameter-free despeckle filter and cleans up the deconvolution noise very nicely.
- Level tweaks: black for each channel separately set to darkest pixel on moon shadow, white to global max (all channels together)
- Gamma: 0.67 0.70 0.60 (RGB) - by eye
- correct for slight purple-green fringing by realigning colours: shift red channel 2/3 pixel up and 1/3 pixel right (blow up image + move + shrink image) - see attached pic.
Result shown in last attached image. I'm quite pleased with the result for my first attempt at this sort of thing.
PS. I kept getting this strange error when trying to open the original tiffs with any image editors I tried: unknown field with tag 317 (0x13d) encountered.
Fixed with a pass-through raw2tiff.
