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HSO  filter image

Filter changer - 

1L/2S/3H/4O/5 clear

30s crude align 

120s needs fine align.

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Calibration frames

Bias - readout noise - lens cap and short exposure

Dark - system noise - lens cap and same exposure time as lights (images)

Flats - vignette - white tee shirt over lap top screen.

Dark flats -noise on flat - lens cap with same exposure time as Flats

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Collect at least 10 long exposures RAW, with darks.  1/4 and 1/10 times for HDR.

Stack images in Deep Sky Stacker - group the different filters and exposure times, stack repeated images  using a common reference selected from best H image. Take non repeating images, use same reference frame, check images in turn and save. Use separate groups for different image sets that DO NOT include reference. Enable 2 x drizzle to eliminate pixelation. 

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In PS assemble HSO layers, change mode to RGB, align, equalize core color area, paste into RGB layers. reset black level, separately merge HDR color images, then merge color and L shorter exposure times.

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Exposure times 

f2 30secs ISO2000 RGB is benchmark for good nebula =  

Filter increases exposure 500x, reduces bkg 6x.   

G30 is ISO 6000 so f2 240s G30 HOS should resolve M8. 

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Example Rosette Nebula HOO image   f2  120secs x 4 frames per channel.  In Wimberly S/N  for Nebula 2.5:1, a 2x improvement with line filters for a M5.5 nebula, background 4 AU. Eagle nebula (pillars of creation M6.0 should increase exposure time to 200 secs. The nebula had a intensity of 10 AU, so darker Bortle or longer exposure for dimmer objects. 

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Example: Elephants Trunk HSO with S level down to loose Green shade.  Adjust hue to get yellow/red contrast in nebula. G30 120s at least 5 frame stack. 

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SCT starburst fix 

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Use short exposures as a mask. Select background - Inverse - Expand to cover starburst - feather the edge - Blur to remove starburst. 

Invert and use this mask for image that gets Sharpen AI Focus / very blurry as noted below. 

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Stacking 

Around 1 hr total exposure, for normal polar align at +- 5 amin produces 1 asec min-1 drift so max exposure 30-60s. For Whirlpool Galaxy C6 SCT/RASA with f2 gain 20 produces usable images. 

 

DSS

 

Center crop Offset X 0, Y 0,  Width  2000, Height 1500  default is at center

 

1) Linearize Luminosity for large dynamic range color rendition 

2) Saturation 15-20% 

3) move RGB to make brightest area background black - should have good color contrast - Save - move to Photoshop

4) Add single exposure underexpose layer - align -opacity 30%

5) Crop and double pixel if needed.

6) Denoise

7) Histogram equalize, align and then trim edges to match edges

8) RAW - White Balance for best balance on full image. 

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At Gain 30 30sec exposure with cooled -20C camera, 1 sigma noise/background signal went from 8% for a single frame to 0.9% (1.3 IU) for 180 frame stack. This is right for Square root (N) statistical sample. ​

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For f2 2 hrs exposure, flatten the luminosity curve to avoid clipping color detail. ​

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Pixinsight 

PIPP SER to FIT

PI Debayer, Calibrate CFA RGB results in a color image. 

Curves Transport - Reduce Green 255 to 165. 

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The first quick thing is to select an unlinked STF (Ctrl-). This will usually generate a reasonably neutral colour-balanced screen image. If you can solve the image (script ImageSolver), you can then call PhotometricColorCalibration (PCC); if this works, it will usually give a good usable color balance to the image. Sadly, in some parts of the sky there are not enough stars in the APASS catalogue for PCC to work, and you will need to use other processes (e.g. BackgroundNeutralization and ColorCalibration).

https://pixinsight.com/forum/index.php?threads/how-to-remove-green-colour-after-osc-stacking.16575/

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PixInsight’s SCNR (Subtractive Chromatic Noise Reduction)

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yeah the technical reason is that STF uses the statistical properties of the image to compute the stretch, and by necessity the SNR of the green channel from any OSC has 2x the SNR of the other channels (because there are always 2 green pixels per bayer quad.) so that fools STF and presents the image as green.

you can just unlink the channels in STF. or, after you've done color calibration to the image, the channels will be properly balanced and running STF with the channels linked will give you a proper looking image. (in fact, after color calibration you absolutely should run STF with linked channels or STF will show you something different than the color calibration step computed.)

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Sharpening 

​​Always eliminate pixelation in RAW before noise reduction or sharpening to eliminate artifacts. 

Photo AI adjust noise reduction to eliminate noise, followed by careful sharpening. 

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When image low noise and edge pixelated or under sampled , then  RAW Gigapixel  worked well in water tower test - - seems to add noise in JPEG's. 

JPEG or frame grab in Premier. resample 2x, Blur at 2 pixels to loose pixelation then  Photo AI / Sharpen (Natural)   -  Soft.  Works really well on dancing grebes. 

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Sharpen AI - focus will try to convert spots to squares so do not use on stars​

Use Sharpen AI - Soft / Very blurry / reduce noise slider - to sharpen and  retain circles. Motion and focus try to change circles to squares. 

Alternatively mask circular stars, Sharpen AI - Focus / Very blurry - to sharpen with mask to retain circles. 

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Image processing

Isolate nebula 

If needed remove stars from nebula - copy nebula, B&W, contrast to isolate stars in nebula, expand 2 pix, delete any stars that are part of nebula, make mask, shift nebula, copy from shift, paste into original nebula, blur to smooth. 

Make nebula transparent.

Make foreground stars - original image, contrast adjust to isolate a few bright stars, delete any associated with nebula. 

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Deep Space look 

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To create realistic deep sky images without blocking stars:

1) Copy master image - set 50% opaque - and move so that that stars pairs are distinct - set transparency 100% opaque.

2) On original - select stars using Astropanel/Astro/Hot pixel/Harder filter.

3) On filter - Create mask using magic wand - adjust tolerance  on background - Contract 1 pixel.

4) Copy filter on moved master to select local backgrounds to each star

5) Reorder layers so copied filter is added to original - Merge layers 

6) Select galaxies-feather - invert-Blur to eliminate residual variation

7)  Apply  levels by moving zero to obtain almost black background - do not overdo !

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TARGETS - Whirlpool , Leo triplet 
 

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Moon Composite 

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Exposure 1/125 ISO 3200  PP7.  Continuous pics with hand controller - 40 or more frames. Lucky stack at 10%. 

Remove background - point / Tolerance 60 Feather 10 

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Visualize corona 

Exposure conditions http://eclipse.gsfc.nasa.gov/SEhelp/eclipsePhoto.html

Example from 2016  1/60 middle corona, 1/20 upper corona. 1/3 outer corona ISO500 1000mm on NikonP1000. Need to be on tripod and need much shorter exposures, use Sony for lower noise. Ay ISO500 1/400 inner corona, diamonds 1/1000, prominences 1/2000 ISO100, chromosphere 1/5000 ISO100, Baileys beads 1/5000 ISO50.

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At ISO100  6 levels - 1/2000 - 1/400 - 1/80 - 1/16 - 1/3 - 1.5 secs prominences to outer corona.  

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Use Nikon for prominences at max. - video for image average. 0.6 degree field  ISO100.

Use Sony on Orion ED80 for corona because solar filter is easy to add. Time lapse  video up to totality and then exposure series, back to video for diamonds. 

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PS function "Find edges" which is a 3x3 kernel, also very noise sensitive and relys on only diff with 1.5 pixel region.

-1 -1 -1

-1  8 -1

-1 -1 -1

Filters/Other/Custom allows custom kernels. 

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Radial blur technique.

Take multiple images RAW  16bit/channel, align and average to minimize noise .

Copy/Paste, on top image, select Subtract, vary radial blur (try 150 pixels) and level (0.5) to see best result. The result is " second differential" with much lower noise. In addition, merge various exposures, and radial blurs. Sharpen and contrast adjust. Probably best with Sony 7as for low noise. Exposure 1/60 at ISO500 for first test.

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"Multiscale Gaussian Normalization" Durkmiller technique

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Produces outstanding detail by using many carefully aligned images to reduce noise. Starts with the radial blur.  It is then normalized by dividing local difference by the local std deviation of difference.  Small standard deviation at the zero crossovers enhances the edges. Now merge with multiple radial blurs and multiple exposures. 

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https://arxiv.org/pdf/1403.6613.pdf

Pseudocode for MGN 1.

1.Replace spurious negative pixels with zero or local mean/median.                                                Image = Ixy

2. Create Gaussian kernel of width wi . Kernel elements should sum to unity.

3. Convolve image with kernel to create local mean image B ⊗ kw.                                                   Ixy mean = Ave 1-n  Ixy

4. Calculate difference between image and the local mean image, square the difference, and convolve with kernel. Square root the resulting image to give ‘local standard deviation’ image σw (Equation (2)).                                                                                            Std xy =   (Ave 1-n ((Ixy - Ixy mean)^2))^0.5

5. Calculate normalized image Ci by subtracting the local mean image and dividing by the local standard deviation image (Equation (1)). Store the result.

     Edges are created where there is an image and low variation i.e. base of edges                          Ci xy=(Ixy -  Ixy mean )/ Std xy

6. Apply arctan transformation on Ci to give C 0 i .                                                                                   C0 xy = scale Ci xy

7. Repeat 2-6 with the different kernel widths wi .

8. Take mean, or weighted mean if preferred, of the C 0 i to give a weighted mean locally-normalised image.

9. Calculate a global gamma-transformed image C 0 g by applying Equation (4).                              Edge image  Cg xy = scale Ixy

10. Sum the weighted mean locally-normalised image with the global normalized image C 0 g , with appropriate weight h (as Equation (5)).  

                                                                                                                                                                            Final I = Cg xy + C0 xy weighted ave. 

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The graphs show a excel simulation of the process on a line image.  Confirming the basic maths of the process. 

Not clear how to get the Stdev in PS. Can get max and min for a pixel area. Max-Min gives a measure of noise, does appear work, needs lower noise.  

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