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About jager945

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  1. Say no more. IMHO, that's not bad at all for Bortle 6 and a 1000D! Light pollution is such a killer for fainter objects. The mod explains how you were able to get the HII areas showing. Nice!
  2. This looks quite good to me. I would have expected a somewhat deeper and more noise free signal for 8.5h though. What instrument did you use to acquire the data? How is the light pollution at your location? I can't quite place Peter's comments about the colours and clipping however... The foreground stars show all temperatures of the black body curves equally (red->orange->yellow->white->blue are all accounted for). The yellow core is present (older stars), the bluer outer rim is correct (younger OB stars, more star formation), the all too often neglected purple/pink HII areas (as can be corroborated/seen here) are just about coming through in the outer rim (responsible for the star formation), the red/brown dust lanes are present. You have produced a scientifically valuable image in terms of coloring of temperatures and emissions. Finally, your histogram looks just fine to me and shows no clipping that I can see; I'd say nicely done!
  3. I'm the muppet here! My apologies - I should've made clear I'm the developer. I usually have this in my signature on other forums. I just updated my profile pic to avoid any confusion in the future. Clear skies!
  4. Hi Paul, You are producing some fairly good data - kudos! Now I could be wrong, but from the color signature (a lack of yellow) I get the impression you are using a light pollution filter. Is that correct? The only obvious thing I can recommend to improve your datasets, woudl be to try dithering between frames, as I can see some walking noise ('streaks'). When processing spiral galaxies, things to look out for are a yellow core (older stars, less star formation), blue outer rim (younger blue stars, more star formation) and purplish/pink HII areas dotted around the arms (you captured these too). You'd also be looking for a good even foreground distribution of star colors, ranging from red->orange->yellow (missing here)->white->blue. You are definitely well on your way! FWIW I processed your image in StarTools 1.5 as follows; --- Auto Develop Default parameters, to see what we are working with. We can see some stacking artifacts, gradients, walking noise, dust donut at the top. --- Crop Cropping away stacking artifacts and dust. Parameter [X1] set to [20 pixels] Parameter [Y1] set to [55 pixels] Parameter [X2] set to [2129 pixels (-16)] Parameter [Y2] set to [1414 pixels (-14)] Image size is 2109 x 1359 --- Wipe Getting rid of gradients. Default parameters. Parameter [Dark Anomaly Filter] set to [4 pixels] --- Auto Develop Final stretch. Clicked and dragged a Region of Interest (RoI) over part of the galaxy. Parameter [Ignore Fine Detail <] set to [2.5 pixels] Parameter [RoI X1] set to [95 pixels] Parameter [RoI Y1] set to [607 pixels] Parameter [RoI X2] set to [1963 pixels (-146)] Parameter [RoI Y2] set to [964 pixels (-395)] --- Deconvolution Auto mask. Default settings. Usually worth a try, as the module tends to "know" when and where improvements can be made. It didn't do too much in this case. --- HDR Default parameters. Shows a little more detail in the core. --- Color See notes above about what to look for. Parameter [Bright Saturation] set to [3.00] (less saturation in the highlights to hide some color channel alignment issues) Parameter [Green Bias Reduce] set to [1.09] Parameter [Red Bias Reduce] set to [2.09] Parameter [Cap Green] set to [100 %] (only when you're done color balancing) --- Wavelet De-Noise Default parameters. Parameter [Grain Dispersion] set to [7.5 pixels] Hope this helps at all!
  5. Hi Danjc, The short version of what's going on; stacking artifacts. Crop them away. They are fairly obvious in the image you posted. The long version; any StarTools tutorial or video will start by telling you to crop away stacking artefacts. The application itself will warn you about them too if they are detected (as it does with the dataset you posted). When you launch the Wipe module without cropping them away, you are effectively asking Wipe to create and subtract a light pollution model where those stacking artifacts are not being clipped (StarTools will virtually never clip your data unless you explicitly allow it to). In order to satisfy this, Wipe creates a model that locally backs off (e.g. locally subtracts no light pollution at all), causing local light pollution remnants around the edges where the stacking artefacts are located. Tutorials can be found here, including a "Quick start" tutorial if you're in a hurry. With regards to your dataset, it is fairly noisy (even when binned), which may make it hard(er) for AutoDev to lock onto the detail. A manual Develop will yield better/easier results in that case. When/if using Wipe, use the Narrowband preset (as of v 1.5) for this H-alpha data. You may not need to use Wipe if your data is well calibrated and there are no obvious gradients and/or bias signals in your dataset. Your dataset is well calibrated, with nothing too obvious in terms of bias signal. You can get something like the above with a simple workflow like this; --- Auto Develop Default values, to see what we got. We can see stacking artefacts (thin lines around all edges), noise, oversampling. --- Bin Converting oversampling into noise reduction. Parameter [Scale] set to [(scale/noise reduction 50.00%)/(400.00%)/(+2.00 bits)] Image size is 1374 x 918 --- Crop Getting rid of stacking artefacts. Parameter [X1] set to [7 pixels] Parameter [Y1] set to [8 pixels] Parameter [X2] set to [1369 pixels (-5)] Parameter [Y2] set to [911 pixels (-7)] Image size is 1362 x 903 --- Wipe Optional, I'd say (see also comments/reasons above). --- Develop Final stretch. Choosing a manual Develop here, AutoDev will have trouble locking onto the finer, fainter detail to to overwhelming noise. Parameter [Digital Development] set to [96.76 %] Parameter [Dark Anomaly Filter] set to [20.0 pixels] --- Deconvolution Usually worth a try. Auto-generate star mask. Only very marginal improvement visible due to signal quality. Parameter [Radius] set to [1.3 pixels] --- Wavelet Sharpen Default parameters. Using same mask that was auto-generated during Decon. --- Wavelet De-Noise Default parameters. Parameter [Grain Size] set to [8.0 pixels] Hope this helps!
  6. AutoDev serves a dual purpose; first it is used to show any defects in your image, then it is used to perform your final global stretch after you have mitigated the issues you found earlier. In the above image, we can see gradients, dust donuts and (rather severe) walking noise. Flats are the #1 way to improve your image (and processing enjoyment! ), with dithering between frames a close 2nd (this solves the walking noise issue). They are really not optional and they don't really cost anything, except some time. Also don't forget you can (should) click and drag a Region of Interest for AutoDev to optimize for (by default the RoI is the entire image). In the case of the image above, a slice of M31, including its core would constitute a good dynamic range sample we'd be interested in. There are also cases where AutoDev simply cannot lock onto celestial detail. These cases usually involve heavy noise and/or lots of "empty" background. The latter can be solved with an RoI. The former can be solved by increasing the "Ignore fine detail <" parameter, which makes AutoDev "blind" to small noise grain. If you cannot fix or work around the calibration/acquisition issues in your dataset and cannot obtain a good result with AutoDev, you can always resort to a manual Develop. As bottletopburly already highlighted though, post-processing becomes infinitely easier and repeatable when you have "good" data. I'm putting "good" between quotes here, because it just means "properly calibrated". It doesn't have to be deep, gradient free or noise free, as long as it has been dithered and properly calibrated with - at least - flats. Hope this helps!
  7. No problem - at the end of the day it's all about what gives you the result you are most happy with! While it is of course futile to argue aesthetics, it is important to understand that noise and signal fidelity are physical properties of a dataset (as well as its intermediate states towards a final image). Workflows, tools and filters all affect noise propagation in different ways as you process your image. Noise and noise propagation, in turn, directly affect how much you can push a dataset; as you know it is far easier to dig out more detail with a cleaner dataset and signal. For that same reason, we endeavor to get longer exposure times - so we can show more detail. Us deep sky AP'ers deal with very faint signal. Noise is the bane of our existence. Noise mitigation is an extremely important part of signal processing. The speckles are just a visual manifestation, whose presence can indeed be left to personal taste. However its mathematical significance is omnipresent with far reaching consequences for the effectiveness of processing steps and their cumulative behavior. TL;DR Noise mitigation strategies employed by your software and its algorithms while you process, allow you to dig out more detail in your final image - it's not just about leaving or removing the speckles in your final image. Glad it helped someone! There is actually a 'home in' button that, once clicked a few times, will bounce between a range suitable for your image. Personally, I rarely use the Develop module (I use AutoDev with an RoI instead), except in cases where I really need to correct something or where AutoDev fails entirely. The latter can happen in the presence of noise, or when data was already stretched prior (AutoDev assumes a linear dataset). Clear skies,
  8. Thank you for uploading the dataset. It is much appreciated. I don't see anything immediately problematic, that would have prevented you from achieving the same result in StarTools only. The dataset is fairly bright, almost as if it has been pre-stretched and is no longer linear. I could be entirely wrong here though. Regardless, here is a simple workflow that was meant to emulate the coloring and result you produced and - presumably - are happy with. Simultaneously, it should hopefully demonstrate the major reason why you would want to include StarTools in your wokflow; superior noise mitigation and signal fidelity. If time vs result is a measure you are primarily concerned with then processing the image took ~10 minutes on a 6-core Xeon from 2010 with an SSD drive. Your mileage may vary obviously depending on hardware and how comfortable you are with operating the software. However, many default parameters and presets applied. StarTools 1.4.352 was used. --- Auto Develop To see what we're working with. We can see the image is quite bright, has a strong green bias + severe gradients, and is oversampled. Noise is already visible. Some stacking artifacts are visible. --- Bin To convert oversampling into noise reduction. Parameter [Scale] set to [(scale/noise reduction 50.00%)/(400.00%)/(+2.00 bits)] Image size is now 2329 x 1782 --- Crop To remove stacking artifacts and frame the galaxy better. Parameter [X1] set to [97 pixels] Parameter [Y1] set to [79 pixels] Parameter [X2] set to [2180 pixels (-149)] Parameter [Y2] set to [1711 pixels (-71)] Image size is now 2083 x 1632 --- Wipe Vignetting preset. Parameter [Dark Anomaly Filter] set to [6 pixels] in order to help Wipe ignore dark noise better. --- Auto Develop We're doing a 2-stage stretch here to achieve a similar stretch to your current image. Parameter [Ignore Fine Detail <] set to [3.3 pixels] to make AutoDev ignore noise Parameter [Outside RoI Influence] set to [5 %] Parameter [RoI X1] set to [755 pixels] Parameter [RoI Y1] set to [568 pixels] Parameter [RoI X2] set to [1336 pixels (-747)] Parameter [RoI Y2] set to [998 pixels (-634)] --- Develop Second stage, bring brightness down again. Parameter [Gamma] set to [0.58] --- Deconvolution Attempting some modest deconvolution. The earlier binning will have created some small areas that now have a high enough signal-to-noise ratio. Parameter [Radius] set to [2.6 pixels] --- HDR Reveal preset. Totally optional, but demonstrates the value of having these sorts of local optimisation tools in your arsenal. Parameter [Detail Size Range] set to [1000 pixels] Parameter [Strength] set to [1.7] --- Color Final color calibration, emulating the style of your current image. Parameter [Style] set to [Artistic, Not Detail Aware] Parameter [Dark Saturation] set to [2.00] Parameter [Bright Saturation] set to [2.30] Parameter [Saturation Amount] set to [365 %] Parameter [Blue Bias Reduce] set to [1.01] Parameter [Green Bias Reduce] set to [1.09] Parameter [Red Bias Reduce] set to [1.42] --- Develop I noticed you prefer a pedestal in your background. Parameter [Skyglow] set to [4 %] --- Wavelet De-Noise Final noise reduction - StarTools has now had the longest time to track (see Tracking feature) noise propagation and is ready to autonomously snuff noise out with per-pixel accuracy. Default parameters, except parameter [Smoothness] set to [82 %] After this short workflow, you should hopefully end up with this; (full res image here) Any questions, do let me know! I hope this short example has helped demonstrate the value of using StarTools in your current workflow, or at the very least demonstrates StarTools to be capable (and lower cost) alternative to other software. Clear skies,
  9. Thank you for the explanation. I'm still holding out hope there this may just be a simple understanding or maybe you are confusing StarTools with another application or action sets for PS? In the case you are indeed talking about StarTools, something appears to be terribly wrong. Have you ever processed an image from start to finish in StarTools in the past, or have you been using it for just one or two features? With regards to coloring, it appears you may have missed the Style and LRGB Method Emulation settings and/or the Saturation Amount slider in the Color module? If you don't like the default Color Constancy rendering style, it's a single click to change it to the style of other applications (e.g those of PI or APP) or even effortlessly emulate the LRGB compositing styles/techniques of Kredner/Kanevsky or Gendler with another click. Color calibration can only be performed on linear data, so perhaps that's where things are going wrong? Are you are aware StarTools performs other - for astrophotography - useful things like deconvolution, local contrast optimisation, local dynamic range optimisation, wavelet sharpening, color constancy and more, none of which are currently - by my knowledge - offered by either PS or APP? Are you familiar with ST's noise propagation Tracking feature? You are certainly not obliged to do so, but if you wish to share your dataset/stack with me, I'd love to prove StarTools' worth in your workflow. Indeed, especially in the area of noise mitigation, the present image may benefit greatly. Depending how challenging the gradients are, Wipe may also be able to clean up the red and green gradient remnants currently visible in the background. Do let me know!
  10. Hi, I'd love to know why you wouldn't recommend anyone use StarTools any longer? Is there a dataset you are having trouble with? (happy to do a personalised tutorial if so!) Thank you! EDIT: I also noticed on astrobin the difference in exposure time between the two images is 5h50m for the new image vs just 1h15m for the old image?
  11. @bottletopburly You're so right. It's kind of unfair for newbies; there is so much to tackle and if acquisition is poor, then post-processing is so much harder. It's a double whammy. What you did was the perfect approach; divide and conquer. i.e. decoupling learning post-processing from learning data acquisition. Perhaps not a video/tutorial, but I thought I'd post this animated GIF here as well. It shows what the years of development between 1.3.5 and 1.4 (to be released soon) have yielded in terms of signal fidelity. It's a 400% enlarged crop of a Jim Misti M8 Hydrogen-alpha dataset that has been intentionally non-linearly "mangled" to put Tracking through its paces. Specifically, it has been stretched, Contrast enhanced, then linearly deconvolved (using Tracking time travel and precognition of future signal evolution), then noise reduced (also using Tracking). Workflow, parameters and settings were kept identical between 1.3.5 and 1.4. The only difference is the algorithms in Decon and Denoise making increasingly more sophisticated use of the Tracking data/time travel over the years (with one unreleased quality bump applied here that hasn't been released yet). ("Original" is signal as visible, without any Tracking-enabled modules applied yet)
  12. Thanks for spreading the word! I'm really hoping the Tracking video helps people understand better what is so incredibly special about ST's processing engine vs traditional applications. Tracking is actually where most of my time, efforts and R&D are spent. The "time-travel" of your signal is why StarTools can/should yield better results with the same data. There are some significant improvements coming up to the Decon module (again!), making even better use of "future knowledge" about your signal. I try to explain it on the website;
  13. Aha! That explains a lot JPEG is an 8-bit lossy image file format, where you camera applies all sorts of processing (stretching, color calibation, sharpening, sometimes noise reduction) before saving it to the card. You'll want to avoid all this. When processing this dataset, however, you can make use of StarTools' ability to "reverse" the stretch JPEG encoding applied (choose "Non-linear sRGB source" when opening the dataset), so at least you can work with somewhat linear data. StarTools' modules should then do a better job across the board. Honestly though, when you manage to grab signal like this in mere lossy 8-bit JPEGs, this bodes very well for your future endeavours! Saving as FITS is the favourite format when it comes to astrophotography datasets, as it is "philosophically" much closer to scientific instrument data, and virtually never used for finished images meant for human consumption. Because you stacked 8-bit JPEGs you probably won't see any fidelity gains using 32-bit FITS, but using a 32-bit FITS file format (Integer is best) for your datasets is good practice. You can find all the steps you took in a file called StarTools.log (should be in the same folder as the executables), so you can precisely replicate them if you need to. As of the 1.4.x beta versions, it also stores the masks in that file, so you can recover them too. They are stored in BASE64 format and look like long text strings. For more info on how to convert these strings back to PNGs you can import as masks, have a look on the StarTools website. (I'm the author of StarTools, therefore I don't think it's appropriate to "spam" direct links to my own website, but it should be easy to find) Getting "closure" on an image becomes easier once you get to know you gear and the characteristics of the datasets you produce with it. You'll start getting a sense of what you "can get away with", how far you can push things, but also - and that's what this hobby is all about - your personal tastes. Also not unimportant - to some - is being able to document and replicate faithfully the physical & chemical properties of the objects you are imaging. Emissions, reflections, temperatures, shockwaves, tidal tails. All objects have a story; a past, a present, a future.
  14. Hi, I can't be totally sure, but it appears to me the dataset has already been non-linearly stretched. If this is the case then, some things like light pollution/gradient removal, color calibration and deconvolution cannot be performed correctly (from a mathematical point of view). StarTools, especially, is sensitive to this, as much of the processing engine effectiveness hinges on being able to reliably track signal evolution from linear source (e.g. 1-to-1 photon counts) to final processed image. When you save the DSS result, try saving with settings "embedded" rather than "applied". This should give you a dataset that is linear. If you already did this, then the problem may lie somewhere else; be sure to stack only RAW files (e.g. CR2, NEF or ARW files), and do not use any intermediary programs before passing the frames to DSS. And, as everyone else already commented; flats, flats, flats! They are the single most effective way of improving your datasets (with dithering between frames a close second). Best of all, it's free (just a bit of effort). Still, nicely done though; galaxies are not easy to capture from a light-polluted environment, and you've actually managed to capture the faint tidal tail! (problem of course is that gradients and unevenness can look like tidal tails as well, that's why flats are so important; they remove the need to engage in subjective processing trickery and let the dataset speak for itself) Good stuff!
  15. Hi, Have a look at the Dell Optiplex 9010 and 9020 series, as well as the HP Elite 8300 series (i7 models). They are regularly sold for (relative) peanuts (check eBay for example - use a coupon if you can find one to get more off the price) once they have been written off by the office, university, government organisation, etc. that - often lightly - used them. The i7 processors in these are very, very capable. They use DDR3 memory which, right now is much cheaper than the overpriced DDR4 memory. Upgrading (if needed) to 16GB of RAM should be very cost effective. These cases are very compact, but an extra 2.5" SSD drive will fit no problem. SSD drive have recently really come down in price. If you don't expect the need to fit a graphics card in the future, these machines are an absolute steal and the (IMO and AFAIK) the most cost-effective way to get your hands on an extremely capable photo editing machine. If you don't have Windows 10 yet, you can get a totally legit OEM keys from eBay for a couple of pounds/dollars; the install media can be downloaded freely from Microsoft. Often times, the machines themselves already come with Windows 10 though. @DaveS If you are getting "out of memory" errors (in any software), you are likely running a 32-bit version of the software, a 32-bit Operating System or your virtual memory settings are incorrectly configured. Modern Operating Systems (and applications) should never really bother you with an "out of memory" error, simply because they use your hard/SSD drive to supplement RAM (this may slow things to a crawl, but should never really result in an "out of memory" error!).
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