This is actually a very good, comprehensive list!
Guy wrote:ther from various sources.
So perhaps I could tell you my general current approach and perhaps you could say how it could be improved:
Current Analysis
(This is aimed at a relative novice like me - but even so I may have gone into too much detail in some places)
After an imaging session - as a minimum start with a set of Lights, Darks & Bias frames.
- - Look at the lights and discard any that are low grade or have individual artefacts that don't appear in the majority of images (e.g. Satellite trails etc, focus issues, cloud, mist - etc -etc)
- Stack the sub-frames
Satellite trails don't have to be a problem, depending on the outlier rejection algorithm you choose during stacking (for example median stacking). This decisions too depends on your circumstances; have you got a lot of time and thus a lot of frames? Can you afford to be picky?
Study the stacked image:
First, look for the problems:
- Check if image has been white balanced [Ivo - Is there an easy way to do this?]
This requires knowing what your software and camera does internally. The latter only white balances if making use of an on-board processing engine (.e.g JPEG), whereas RAW will not be white balanced.
DSS insists on white balancing, whereas PixInsight does not.
Though not scientific or always accurate, it's often easy to see whether data has been white balanced or not with a lot of cameras; a green/teal bias is often visible. White balanced images often show a red or yellow bias.
- look at the overall image - are there areas where there are colour casts or vignetting? if so plan to use the Wipe tool
- Use AutoDev module and look at initial image - this will show up any colour casts and vignetting well.
- Sampling - is the resolution better than the seeing? (over-sampled) [How do you identify this from the image?]- use Bin module to reduce resolution and increase SNR
Simple - if the image, zoomed in looks "blurry" then more pixels than necessary are used to describe the detail in your image. Your image is then oversampled.
- Zoom in and look at the background - Look for shadows and marks that could indicate dust or scratches - make a note to try the Heal tool
- Look at noise:
- Is there a lot of noise?
- zoom in - does it have a colour bias (light pollution?) or random (equipment generated?)?
- Are there signs hot pixels have not been eliminated before stacking?
- Is the noise level such that a binned image would look better? [Ivo, Is this sensible - any tips on how to decide?]
In AP, the noise level is
always such that a binned image would look better.
There is always more detail just over the horizon, waiting to be brought out, if only your data was that little bit better.
At the end of the day, it's up to you to decide of course. If you want a deep, high-fidelity post stamp, that's your artistic prerogative. The cool thing is that binning gives you that freedom to make that trade-off.
[The whole area of identifying types of noise and how best to correct it in post-processing is a bit of a 'black-art' to me. Any tips?][/list]
I could fill pages on this topic, but in most cases by far the biggest noise type is shot noise (
aka Poisson noise).
"Correcting" this type of noise is not really possible as such - this noise is fundamentally 'uncertainty' in your signal. We can, however, (in all sorts of clever ways) pretend that uncertainty is not there by making educated guesses about what the signal would look like if we modeled that uncertainty and then removed it. You are spot on when you say you feel it's a black art - it very much is. There are no right answers. No one can tell you what is "too much" noise reduction or "too little".
The only unique thing that StarTools does versus any other software (that I know of) is that it makes sure to keep an exact handle on that modeled uncertainty at all times, even when your data is being processed, stretched and modified. Therefore noise reduction in ST is using the right model at all times, applicable to the image as you currently see it. This in turn makes for extremely targeted noise reduction across the image. E.g. noise grain (uncertainty) in the darker areas that are, for example, stretched more than the highlights are noise reduced more precisely because those areas contain more uncertainty after they have been stretched.
- Look for banding - vertical or horizontal - Auto Dev module may show this - plan to try Band tool to fix
- Look at the stars and other features:
- Signs of Chromatic aberration - try using Lens or Filter module later
- Signs of Purple fringing? - try using Lens or Filter module later
- Look at the stars in the centre of the image - are they round or elongated?
- if elongated then look back at the sub-frames and see if they are all the same or if some are worse than others - re-stack if necessary.
- if all the same then general problem (guiding problems?) see if you can fix for next time. For now plan to try the Repair tool.
- if round but blurred or doughnuts - see if all subs are the same - discard sub(s) and restack if necessary.
- if all the same think about what might cause this (e.g. poor focus) and try and put it right for next time. For now plan to use the Decon module.
- Look at the stars at the edge - is there coma (stars elongated on axis towards the centre) - as opposed to star trails?
- Make a note to use the Lens tool to reduce this before doing any cropping of the image.)
- Look at the Luminance histogram - is there much saturation? Could it have done with longer exposure/ more subs?
[What other things to look for?]
If applicable, I would add determining the optimum ISO value for your camera to the above. ISO is a bit of an artificial thing in the digital age, since digital sensors only really have one sensitivity factor. Analog and digital circuitry artificially modifies the sensor's behavior (for example emulating a higher sensitivity by" counting" 2 photons for every real photon that is recorded), but the sensor's inherent sensitivity cannot be changed. It's a bit of a long story, but in a (somewhat simplified nutshell) the ISO where the sensor is not artificially "throttled", nor "boosted" is the ISO you should be recording at.
- Look at the RGB histogram - is there saturation/clipping of colours? Is there much green? [What other things to look for?] This will also show up in 'Max RGB' tool in the Color module.
If you haven't come across this yet, the
Color module documentation has some pointers, specifically;
White balancing by known features and processes
StarTools' Color Constancy feature makes it much easier to see colours and spot processes, interactions, emissions and chemical composition in objects. In fact, the Color Constancy feature makes colouring comparable between different exposure lengths and different gear. This allows for the user to start spotting colours repeating in different features of comparable objects. Such features are, for example, the yellow cores of galaxies (due to the relative over representation of older stars as a result of gas depletion), the bluer outer rims of galaxies (due to the relative over representation of bright blue young stars as a result of the abundance of gas) and the pink/purplish HII area 'blobs' in their discs. Red/brown (white light filtered by dust) dust lanes complement a typical galaxy's rendering.
Similarly, HII areas in our own galaxy (e.g. most nebulae), while in StarTools Color Constancy Style mode, display the exact same colour signature found in the galaxies; a pink/purple as a result of predominantly deep red Hydrogen-alpha emissions mixed with much weaker blue/green
emissions of Hydrogen-beta and Oxygen-III emissions and (more dominantly) reflected blue star light from bright young blue giants who are often born in these areas, and shape the gas around them.
M101 exhibiting a nice yellow core, bluer outer regions, red/brown dust lanes and purple HII knots, while the foreground stars show a good distribution of color temperatures from red to orange, yellow, white to blue.
Dusty areas where the bright blue giants have 'boiled away' the Hydrogen through radiation pressure (for example the Pleiades) reflect the blue star light of any surviving stars, becoming distinctly blue reflection nebulae. Sometimes gradients can be spotted where (gas-rich) purple gives away to (gas-poor) blue (for example the Rosette core) as this process is caught in the act.
Diffraction spikes, while artefacts, also can be of great help when calibrating colours; the "rainbow" patterns (though skewed by the dominant colour of the star whose light is being diffracted) should show a nice continuum of colouring.
Finally, star temperatures, in a wide enough field, should be evenly distributed; the amount of red, orange, yellow, white and blue stars should be roughly equal. If any of these colors are missing or are over-represented we know the colour balance is off.
Now look at the qualities of the image:
The intention here is to plan about how to process the data:
[This area is not clear to me - any advice you can give would be appreciated]
- Are there any reasons to use something other than a 'standard' workflow? [If so - what are they?]
A "standard" workflow is very personal. I you need to deviate from your standard workflow, it's a sign that something is out of the ordinary (not necessarily something bad of course).
Things "out of the ordinary" may be;
- shooting from a different location (light pollution levels)
- shooting at different times (moon out)
- atmospheric conditions
- equipment change or retuning (for example mount, flexure, insertion of filter in optical train, etc.)
- object characteristics (high dynamic range, low dynamic range, faintness, etc.)
- non-celestial detail (mountain range, trees, dust specks/donuts)
...or whatever makes an imaging session/circumstances markedly different to the ones preceding it.
- Dynamic Range - is it very high dynamic range - are there saturated areas? - use HDR module - or merge 2 images with different exposure times (need to capture more data)
- Colours - what colours are there?
- are they real - how to ensure they are preserved during processing? or
- are they artificial - how to remove?
- Details - are there specific features you want to bring out?
- Image framing - does the image need to be cropped - for framing or to get rid of edge effects?
This is as far as I have got - a lot of detail in some areas - little in others - and perhaps based on misunderstandings.
I have put any specific questions I have in [] but please add to or correct it as you see fit.
Thanks and regards,
Guy
Again, this is a fantastic list and quite possibly worth turning into an article or stickied post.
Thank
you!