Guy wrote:I have been looking for a methodical approach to assessing images to answer the following questions:
- What are the strengths and weaknesses of the image?
- How should I change my processing workflow based on this assessment?
Have these issues been covered by a subsequent video or elsewhere? If not, do you have any advice you can give?
You can get great images with even the simplest gear by just getting to the bottom of two things; 1. why does my image/data look like it does, 2. what should my finished image ideally look like.
Addressing #1 will help you get to know your gear and the unique challenges that your gear and circumstances pose. Once you completely understand how your gear and circumstances make #2 look like #1, you will fundamentally understand each and every challenge that you need to tackle, i.e. undoing or mitigating the individual things that make #2 look like #1. These things will be unique for everyone. Understand them though and all of a sudden image processing will become a 'zen' like experience - I promise! The goal here is to take the guesswork out of it all. All of a sudden you're free to get directly hands-on with your artistic interpretation and vision for the image.
So, try to understand all the possible sources that generate photons that make it to the wells of your CCD. Try to understand how these sources are distorted themselves (ex. atmospheric turbulence). Try to understand how the photons arrive at the aperture of your scope, how they are diffracted, how they are focused, what sort of aberrations your optical system exhibits, how you've tried to remedy these aberrations, how you're filtering any photons. Then try to understand how the photons arrive at the imaging plane, how your CCD converts them into electrons that are stored in wells, whether your CDD's resolution will be over or under sampling the scene, how your camera's circuitry then reads the amount of electrons in each well, how this reading is converted into a digital value, how this digital value is stored as a pixel in a 2D array of pixels, how the 2D array is demosaiced in case of a color filter, how multiple 2D arrays are aligned and stacked, how the stacking reduces noise, how the selected statistical rejection method works, etc.
At each of these steps (and many more), imbalances, noise, inefficiencies, etc. can arise. Identify and learn to spot them or their hallmarks, and find a software or hardware solution that eliminates or ameliorates them.
Spend some time learning about #2 as well. What is it that I'm really imaging here? What's its story? What are its interesting features? What is it made of? How do other people portray it?
Is there a central star to that planetary nebula that you should bring out? Are there any interesting gas knots or distributions in that nebula? Is my image showing emission line colors correctly in that nebula? Is my image showing star temperatures correctly? What's the star age (and correlated temperature) distribution in that galaxy's core and outer rim? Any faint features I should know about that I might have captured? Any interesting interactions between these two galaxies I'm imaging? What's that object's dynamic range? Should I even bother imaging that nebula in N2 narrow band? etc.
Know the answer to #1 and #2 and image processing becomes almost trivial and replicable - a means to an end, a means to get from A to B, not something you get lost in.
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:
(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
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?]
- 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
- 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?]
[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?]
- 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:
- Look at the stars in the centre of the image - are they round or elongated?
- 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 at the edge - is there coma (stars elongated on axis towards the centre) - as opposed to star trails?
- 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 Luminance histogram - is there much saturation? Could it have done with longer exposure/ more subs?
- Make a note to use the Lens tool to reduce this before doing any cropping of the image.)
[What other things to look for?]
- 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.
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?]
- 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?
- Details - are there specific features you want to bring out?
- are they real - how to ensure they are preserved during processing? or
- are they artificial - how to remove?
- 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,
Users browsing this forum: No registered users and 1 guest