SMALL CORRECTION - my stretched image is NON-LINEAR .. not linear like I say in the video and I shouldn't have left the deepSNR box ticked... thanks for calling me out on my error! The speckle however likely doesn't come from this but from DeepSNR being trained on drizzled noise scales which @Ekuy1 notes in the comments. Scaling down matched the noise scale so the model was better able to denoise smoothly - interesting!
dsnr is trained on properly drizzled data, and doesn't work well on standard integrations. this is because proper drizzle has scale 1 noise, where each pixel's noise profile is independent of the surrounding pixels (its more complicated but go with this for now), while standard integrations use various interpolation methods which will cause larger scale noise profiles, such as 2 or 4 pixel noise. due to the nature of dsnr, these clusters in the noise will be mistaken for stars, which will cause the "speckling" you see here. by resampling data down by 2x which has improperly interpolated, 2-pixel noise profiles, like you've done here, you essentially reduce the noise scale to single pixels, which is what dsnr has been trained on, and recognises as well pre-processed data. if you want your images at full resolution, and not scaled down, use WBPP drizzle, or another algorithm which *correctly* implements drizzle integration (Siril and DSS drizzle do not work, they still use surrounding-dependent interpolation), then dsnr will work perfectly well on full-resolution images, just like the results you're currently getting right now. also, drizzle definitely DOES work on CFA (or debayered) images, but likewise, it needs to be correctly drizzled. p.s. lots of misinformation and misconceptions around the drizzle and deepsnr algorithms on cloudynights, if you want to learn more, read the source documentation from the authors "Variable-Pixel Linear Reconstruction"
Ok that's very elucidating thanks! Mine wasn't a perfect scale because the drizzled image is 12,560 which I cropped in slightly first.. *then* resized to 4096 (so god knows what the division is) and then got the speckle.. then resampled from that to 2048 where it worked. But it sounds like I got close enough and what you're saying makes sense. That means it wasn't the "linear" checkbox after all - thank you!
@@DylanODonnell yeah, i would definitely recommend using drizzle during the pre-processing (stacking) workflow. WBPP is the best that ive used, and drizzle also has many other benefits as it was developed for hubble (ill list them below if youre interested). however drizzle integration is process intensive, and time consuming, ive had WBPP crash many times while running drizzle, due to insufficient memory (only have 32GB). as for your current data, you can try software binning it by 2x, or 4x exactly, because then it doesn't have to undergo any of the weird sampling stuff which happens when you input a custom resolution. make sure to select bilinear interpolation mode, so you are literally just taking 4 pixels and averaging them into 1. this way maybe you can save some resolution, but still get a good result with your current stack, but the best method is still to drizzle. another thing you could try is to actually add noise. it sounds weird but it can work. if you add gaussian noise using pixinsight's "NoiseGenerator" process, deepsnr can actually work well on that, it was the original method of using dsnr on mono data before someone thought up creating 3 independent stacks, but it can save colour data too! if you're interested here are some of the reasons why drizzle was developed for the HST - It preserves photometry and resolution of the input image (remember the scales of noise i talked about earlier? this clumping affects your whole image, so your resolution is compromised in standard integrations!) - drizzle weighs input image pixels based on their statistical significance, and so removes effects of geometric distortion on photometry. however im not sure if this is properly implemented into amateur preprocessing software. im sure theres people who know more than me that could tell you
if you CFA drizzle your data at 1x then the dots disappear when using DeepSNR so you can CFA drizzle your 10000 pixel-wide image at 1x and keep it at 10000 pixels wide and still get the super clean result :)
Wow !! That software is so good !! Why do we even need telescopes ANYMORE !! Just take a picture through your binoculars with your IPhone and PRESS THE HUBBLE BUTTON in our AI software !! LOVING IT !! 😅
Another question please sir: Is "Astro Pixel Processor" still a good choice as an integrated astro imaging software package? Or, is it a bit dated now with less flexibility? I'm using Siril right now and find that it works, but would like better use of third-party plug-ins. Thanks again, Michael
Thanks Dylan will check this out. Can you do a video on resampling and sizes as you mention here I am not doing this with drizzled data and you are making me think I should be? Thanks
DeepSNR is a great tool. I’m just eagerly waiting for gray scale support because I don’t want to have to run 3 separate integrations and run it on an rgb combination of that.
Dylan, with pixinsight's WBPP stacking menu, use these settings- Drizzle scale 1x Drop Shrink 0.85 Varshape = 1.5 Grid Size is variable based on dither distance. I dither 30px at 0.58"/Px, so I use Grid Size of 8. if you're under that, consider 16, or even 24 or 32. Increased Dither with Drizzle and DeepSNR will give you a massive boost in SNR and detail, I've measured an increase of ~5-10% in both sharpness and SNR, plus you get the ultra clean drizzle background.
I'm using a 294MC sensor with a Bintel 200mm Reflector. On NGC 6744 at 8288px both struggle to make any difference of value in the process, buttttt.... if I resample to just 50% both programs work a treat..... blur still taking the win tho for detail retained with one shot colour I find.
I had to re-watch with CC on to make sure I was hearing it right. You called it linear data (and the image title says linear) but you also said you had stretched it and used HT. In the next couple of sentences you called it non-linear which it seems to be since if it was linear and you were using STF the green bar would be showing. But when you ran the tool you kept the linear box checked which may or may not have impacted the results. A little confusing.
Is there a reason you didn’t compare it to NoiseXTerminator? That seems such a logical point of comparison. (FWIW I use BXT on my images while linear and NXT and SXT at the end on nonlinear images; I never drizzle or down-sample.)
I never liked Topaz noise reduction. The biggest problem to be fair was probably my own inexperience and the fact I was running it on an older computer and OS which although according to Topaz was compatible, was not really up to it. When I upgraded to a new and much more powerful laptop with Windows 11 I started using Noise Exterminator which I find gives much better results. I bought this as a package with the star and gradient exterminator plugins which also work very well, I would have liked to have bought blur exterminator as well but as I don't use Pixinsight it wouldn't work. Nice image of M83, DeepSNR does look to give great results.
Haven't used it yet, but I do use BlurX. But I'm very careful with that tool, especially with sharpening the stars, BlurX is usually too harsh so I set that very very low like 0,03-5.
@@DylanODonnellit works great for OSC if you make sure to specify in WBPP you are using CFA images in the calibration tab and do a 1x drizzle with a drop shrink of 0.6 to 0.9 (it will automatically do a CFA drizzle)
Can you please try attaching one of your astro cameras to a kids telescope and take some astro photos, tracked of course, maybe you can get your hands on a shitty Tasco telescope from years ago.
Speaking of Tasco telescopes, unbelievably last year a retro shop down the street from my local pub that specializes in 1970s' stuff here in the UK had a 60mm alt-az mounted one on sale for, wait for it, £400. I fell over laughing until I walked passed a few days later to see it had been sold. I don't know who parted with good money for that piece of junk but I hope it was not someone who had just become interested in astronomy and was buying their first scope.
@@KevinRudd-w8s I had two or three Tasco's, two 60mm refractors and a 4inch reflector, after that experience I did not go anywhere near another telescope for 15 years. Telescopes like that destroy the hobby.
This is cool, I definitely need to try DeepSNR and downscaling earlier in the process. Disclaimer: I have *NO* idea what I'm doing most of the time lol. I usually start out with a bit of BlurX followed my NoiseX as the first two steps in processing. I'm nowhere near the level of astrophotographer as you are, but it seems like a good thing to do before using StarX or doing any stretching. Lately my processing has involved a lot of experimentation with the order of things I do to see what works best but I can't really land on a solid permanent order. After some basic stretching on both stars and background independently, I'll take things into photoshop where I'm a bit more familiar to finalize as separate layers. One of my last steps is usually hitting the background layer with another bit of NoiseX or Topaz and I'll play around with them both to see what I like better. I don't normally downscale until I'm exporting a final I’mage because I like the option of having a full resolution photo in case I need it later while being able to export smaller sizes for social media at the same time. Sometimes I wish there was an easy was to process every image the same way, but I guess if it was easy then everyone would do it.
Thanks! And yes my workflow will change from image to image a little depending on what it needs. I definitely find these steps work best at the end after getting to the scale you want for screen .. I don’t know why exactly but it’s worth experimenting in your workflow to test.
I just tried this on a non-linear image and it worked beautifully! I had Starnet set up for GPU acceleration and this used the GPU as well with just a normal installation. Great software!
Based on y our video, I just downloaded DeepSNR and tried it out. I had previously configured Startnet2 and BXT to use GPU acceleration on Linux (and provided a simplified process online) I verified using the nvidia-settings tool in Linux that it was spiking my GPU to 75% utilization. So I assume if you have tensorflow already GPU accelerated, you automatically get GPU acceeleration for DeepSNR as well.
@@leonim513I typically try both before and after stretch and resize, and it always works best after downsampling and stretching .. which is what I was saying. It may be the huge 12,000px size of my drizzled image that blurx, and starnet and deepsnr all do poorly with. That’s why I mentioned them all together.
Lotta people using graxpert .. my results have been mixed but I may be using it wrong. However deepsnr is fairly new so expect OSC support eventually :)
Hey Dylan, I like how you added your butt crack for like half a second in the intro scene, I laughed. I have pretty much abandoned Topaz for blur exterminator. Is this new process better than blur exterminator?
I have been using both in conservative amounts at the end because they both have qualities I like (topaz for denoise and blurx for sharpening. I’d typically sharpen first because that introduces noise then denoise last to remove it.
@@DylanODonnell That's interesting. I typically run Noise Xterminator first, then do a couple of other things, then run Blur Xterminator. I'll try it the other way around, makes sense to me.
@@DylanODonnell I was using Russell Crowman's experimental PixInsight repository which bypassed having to install all the cuda toolkit etc. Maybe thats why it broke my cuda acceleration. Anyways, i've just spent 30 mins downloading and installing the full version as I couldn't get Russel's version to work again
I’ve been using this tool almost since it came out, and there are tricks to get it working well every time. First you must dither, then your drop shrink size is paramount for this to work well. This depends a lot on your pixel scale and camera. In the DeepSkyCollective (I process a lot of images for the group) we use drop shrink of 0.35 and varshap 1.5. I found this works very well for my image scale (1.05) when I drizzle 2x. If I use the regular 0.9 square drizzle I get these speckles like you. But only at drizzle 2x at drizzle 1x they are gone… so it requires a little trial and error. There is also a trick to use this on single mono images that are not combined. Essentially you need to create 3 separate stack for that filter, combine in RGB, denoise then convert to greyscale. You shouldn’t have to reduce the size like you are doing to denoise using this… you really want to apply this early, just after deconvolution.. you should check Charles tutorial on this www.nightphotons.com/guides/single-channel-denoise you should also check the DSC suite which helps with creating triple stacks easily pixinsight.com/forum/index.php?threads/🌍-announcing-the-dsc-processing-suite-empowering-collaborative-projects-🌎.22833/
I was very happy photographing M83 with my 6" Newtonian and you ruined my night. Thanks but I didn't need to see that impressive image right now xD 🙈😅 I'm going to try it with Ha because I was doing RGB. Thanks for the idea Greetings from Argentina
No osc cameras, no independent interface ( you HAVE to have PI ), no gpu acceleration. For me that uses OSC camera, Siril and Affinity Photo sounds great! 😭
have you tried graxpert?, it does background removal and denoise. I've used it with OSC data and other processing with siril and gimp. Also had the same issues with the spotty pixels when you run it on large image sizes so i'm not going to claim it's perfect. It is free though and runs independently so you don't need PI.
![NOSFERATU - Official Trailer [HD] - Only In Theaters December 25](http://i.ytimg.com/vi/nulvWqYUM8k/mqdefault.jpg)
SMALL CORRECTION - my stretched image is NON-LINEAR .. not linear like I say in the video and I shouldn't have left the deepSNR box ticked... thanks for calling me out on my error!
The speckle however likely doesn't come from this but from DeepSNR being trained on drizzled noise scales which @Ekuy1 notes in the comments. Scaling down matched the noise scale so the model was better able to denoise smoothly - interesting!
Are you going to photograph M58 to test deepSNR without the linear data option? 🤔
dsnr is trained on properly drizzled data, and doesn't work well on standard integrations. this is because proper drizzle has scale 1 noise, where each pixel's noise profile is independent of the surrounding pixels (its more complicated but go with this for now), while standard integrations use various interpolation methods which will cause larger scale noise profiles, such as 2 or 4 pixel noise. due to the nature of dsnr, these clusters in the noise will be mistaken for stars, which will cause the "speckling" you see here. by resampling data down by 2x which has improperly interpolated, 2-pixel noise profiles, like you've done here, you essentially reduce the noise scale to single pixels, which is what dsnr has been trained on, and recognises as well pre-processed data. if you want your images at full resolution, and not scaled down, use WBPP drizzle, or another algorithm which *correctly* implements drizzle integration (Siril and DSS drizzle do not work, they still use surrounding-dependent interpolation), then dsnr will work perfectly well on full-resolution images, just like the results you're currently getting right now.
also, drizzle definitely DOES work on CFA (or debayered) images, but likewise, it needs to be correctly drizzled.
p.s. lots of misinformation and misconceptions around the drizzle and deepsnr algorithms on cloudynights, if you want to learn more, read the source documentation from the authors "Variable-Pixel Linear Reconstruction"
Ok that's very elucidating thanks! Mine wasn't a perfect scale because the drizzled image is 12,560 which I cropped in slightly first.. *then* resized to 4096 (so god knows what the division is) and then got the speckle.. then resampled from that to 2048 where it worked. But it sounds like I got close enough and what you're saying makes sense. That means it wasn't the "linear" checkbox after all - thank you!
@@DylanODonnell yeah, i would definitely recommend using drizzle during the pre-processing (stacking) workflow. WBPP is the best that ive used, and drizzle also has many other benefits as it was developed for hubble (ill list them below if youre interested). however drizzle integration is process intensive, and time consuming, ive had WBPP crash many times while running drizzle, due to insufficient memory (only have 32GB).
as for your current data, you can try software binning it by 2x, or 4x exactly, because then it doesn't have to undergo any of the weird sampling stuff which happens when you input a custom resolution. make sure to select bilinear interpolation mode, so you are literally just taking 4 pixels and averaging them into 1. this way maybe you can save some resolution, but still get a good result with your current stack, but the best method is still to drizzle.
another thing you could try is to actually add noise. it sounds weird but it can work. if you add gaussian noise using pixinsight's "NoiseGenerator" process, deepsnr can actually work well on that, it was the original method of using dsnr on mono data before someone thought up creating 3 independent stacks, but it can save colour data too!
if you're interested here are some of the reasons why drizzle was developed for the HST
- It preserves photometry and resolution of the input image (remember the scales of noise i talked about earlier? this clumping affects your whole image, so your resolution is compromised in standard integrations!)
- drizzle weighs input image pixels based on their statistical significance, and so removes effects of geometric distortion on photometry. however im not sure if this is properly implemented into amateur preprocessing software. im sure theres people who know more than me that could tell you
@@DylanODonnell dont mind me yapping for ages 😭
I do drizzle .. not sure if I wasn’t clear on that .. I always drizzle .. I have a video about that too :)
@@DylanODonnell what algorithm do you use. wbpp?
if you CFA drizzle your data at 1x then the dots disappear when using DeepSNR so you can CFA drizzle your 10000 pixel-wide image at 1x and keep it at 10000 pixels wide and still get the super clean result :)
Loving the more regular content mate, keep em coming
Thanks!
Wow !! That software is so good !! Why do we even need telescopes ANYMORE !! Just take a picture through your binoculars with your
IPhone and PRESS THE HUBBLE BUTTON in our AI software !! LOVING IT !! 😅
Another question please sir: Is "Astro Pixel Processor" still a good choice as an integrated astro imaging software package? Or, is it a bit dated now with less flexibility? I'm using Siril right now and find that it works, but would like better use of third-party plug-ins. Thanks again, Michael
I wish it is released as a stand-alone soon, especially with GPU-acceleration and Siril integration
Thanks Dylan will check this out. Can you do a video on resampling and sizes as you mention here I am not doing this with drizzled data and you are making me think I should be? Thanks
DeepSNR is a great tool. I’m just eagerly waiting for gray scale support because I don’t want to have to run 3 separate integrations and run it on an rgb combination of that.
Beautiful image, Dylan! The nebulae you capture in there with HaGB are stunning!
Thanks!
Dylan, with pixinsight's WBPP stacking menu, use these settings-
Drizzle scale 1x
Drop Shrink 0.85
Varshape = 1.5
Grid Size is variable based on dither distance. I dither 30px at 0.58"/Px, so I use Grid Size of 8. if you're under that, consider 16, or even 24 or 32.
Increased Dither with Drizzle and DeepSNR will give you a massive boost in SNR and detail, I've measured an increase of ~5-10% in both sharpness and SNR, plus you get the ultra clean drizzle background.
Thanks for the tip !
How do you work for an Australian astro vendor and promote an American vendor? I guess you are private IT and you have done some work for Bintel?
Yeh I don’t work for Bintel. I own a digital agency. Also my audience are like 90% American !
I'm using a 294MC sensor with a Bintel 200mm Reflector. On NGC 6744 at 8288px both struggle to make any difference of value in the process, buttttt.... if I resample to just 50% both programs work a treat..... blur still taking the win tho for detail retained with one shot colour I find.
Good to hear you’ve noticed the same thing !
@@DylanODonnell 75% gives a natural background without further processing I just tested.
I had to re-watch with CC on to make sure I was hearing it right. You called it linear data (and the image title says linear) but you also said you had stretched it and used HT. In the next couple of sentences you called it non-linear which it seems to be since if it was linear and you were using STF the green bar would be showing. But when you ran the tool you kept the linear box checked which may or may not have impacted the results. A little confusing.
I caught that too. Maybe linear is non-linear down under? Bad joke.. lol.
You are absolutely correct and I am at fault here for mixing them up .. I've pinned a correction :)
Is there a reason you didn’t compare it to NoiseXTerminator? That seems such a logical point of comparison. (FWIW I use BXT on my images while linear and NXT and SXT at the end on nonlinear images; I never drizzle or down-sample.)
Great vid, as always! Looks like another good plug-in for my PixInsight. Thanks, buddy.
I never liked Topaz noise reduction. The biggest problem to be fair was probably my own inexperience and the fact I was running it on an older computer and OS which although according to Topaz was compatible, was not really up to it. When I upgraded to a new and much more powerful laptop with Windows 11 I started using Noise Exterminator which I find gives much better results. I bought this as a package with the star and gradient exterminator plugins which also work very well, I would have liked to have bought blur exterminator as well but as I don't use Pixinsight it wouldn't work.
Nice image of M83, DeepSNR does look to give great results.
Haven't used it yet, but I do use BlurX. But I'm very careful with that tool, especially with sharpening the stars, BlurX is usually too harsh so I set that very very low like 0,03-5.
Thx for the educational video Dylan, from Argentina, another southern Chad sky
Not for osc then? Im using Grad Xpert denoise currently. Is it as good as Noise Xterminator?
I haven’t compared 1:1 but it sounds like the author is working on OSC support
@@DylanODonnellit works great for OSC if you make sure to specify in WBPP you are using CFA images in the calibration tab and do a 1x drizzle with a drop shrink of 0.6 to 0.9 (it will automatically do a CFA drizzle)
Down sampling indeed makes everything better. 🎉
Can you please try attaching one of your astro cameras to a kids telescope and take some astro photos, tracked of course, maybe you can get your hands on a shitty Tasco telescope from years ago.
Speaking of Tasco telescopes, unbelievably last year a retro shop down the street from my local pub that specializes in 1970s' stuff here in the UK had a 60mm alt-az mounted one on sale for, wait for it, £400. I fell over laughing until I walked passed a few days later to see it had been sold. I don't know who parted with good money for that piece of junk but I hope it was not someone who had just become interested in astronomy and was buying their first scope.
@@KevinRudd-w8s I had two or three Tasco's, two 60mm refractors and a 4inch reflector, after that experience I did not go anywhere near another telescope for 15 years. Telescopes like that destroy the hobby.
Goin' deep again! woohoo!
Comment for DoD
Wah😢. We lost space Gandalf today.
I just read :( he was a wonderful man and an amazing presenter at star stuff. I’ll miss him.
Graxpert now has noise reduction it it.. give it a look
This is cool, I definitely need to try DeepSNR and downscaling earlier in the process.
Disclaimer: I have *NO* idea what I'm doing most of the time lol.
I usually start out with a bit of BlurX followed my NoiseX as the first two steps in processing. I'm nowhere near the level of astrophotographer as you are, but it seems like a good thing to do before using StarX or doing any stretching. Lately my processing has involved a lot of experimentation with the order of things I do to see what works best but I can't really land on a solid permanent order. After some basic stretching on both stars and background independently, I'll take things into photoshop where I'm a bit more familiar to finalize as separate layers. One of my last steps is usually hitting the background layer with another bit of NoiseX or Topaz and I'll play around with them both to see what I like better. I don't normally downscale until I'm exporting a final I’mage because I like the option of having a full resolution photo in case I need it later while being able to export smaller sizes for social media at the same time. Sometimes I wish there was an easy was to process every image the same way, but I guess if it was easy then everyone would do it.
Thanks! And yes my workflow will change from image to image a little depending on what it needs. I definitely find these steps work best at the end after getting to the scale you want for screen .. I don’t know why exactly but it’s worth experimenting in your workflow to test.
I just tried this on a non-linear image and it worked beautifully! I had Starnet set up for GPU acceleration and this used the GPU as well with just a normal installation. Great software!
It’s great huh! You’re the second person who’s said GPU acceleration worked .. neat!
Based on y our video, I just downloaded DeepSNR and tried it out. I had previously configured Startnet2 and BXT to use GPU acceleration on Linux (and provided a simplified process online) I verified using the nvidia-settings tool in Linux that it was spiking my GPU to 75% utilization. So I assume if you have tensorflow already GPU accelerated, you automatically get GPU acceeleration for DeepSNR as well.
Ahh I imagined that could be the case.. that's great! It's quite slow without it. I could never get the Star Net GPU acceleration to work!
DeepSNR is good, but why are you comparing it to BlurX, a deconvolution tool, and not NoiseX?
I compared it to topaz? I was talking generally about AI based tools generally when I added blurX at the end as a matter of workflow.
@@DylanODonnell I rewatched that part - fair, but I'm still not sure why you'd run BlurX on a nonlinear image.
@@leonim513I typically try both before and after stretch and resize, and it always works best after downsampling and stretching .. which is what I was saying. It may be the huge 12,000px size of my drizzled image that blurx, and starnet and deepsnr all do poorly with. That’s why I mentioned them all together.
@@DylanODonnell That's fair, and since tone doesn't come across in text well, I was asking from pure curiosity - not trying to criticize.
@@leonim513yeh man all good :)
Great video, instructive and clear! I was wondering if this software can also be installed in Siril...?
The author is working on updates so maybe !
I saw u say it’s good on discord lol
Thanks /r/astrophotography :)
@@DylanODonnell yeaahh
Lovely image . Isn't it around 12 hours total integration ?
You’re absolutely right. King of the fact checkers! I can’t update the video but I’ve updated my socials and blog etc. thank you!
Thank you for teaching me over the last 4 yrs I have been loving this astro stuff! There are a couple others as well but wanted to say Thanks!
Hey mate thanks for saying so !
Another great video! Question, please: What de-noising software would you recommend for color cameras (ASI585MC PRO) using Siril? Thanks, Michael
Lotta people using graxpert .. my results have been mixed but I may be using it wrong. However deepsnr is fairly new so expect OSC support eventually :)
Thanks for your near instant reply!@@DylanODonnell
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Hey Dylan, I like how you added your butt crack for like half a second in the intro scene, I laughed. I have pretty much abandoned Topaz for blur exterminator. Is this new process better than blur exterminator?
I have been using both in conservative amounts at the end because they both have qualities I like (topaz for denoise and blurx for sharpening. I’d typically sharpen first because that introduces noise then denoise last to remove it.
@@DylanODonnell That's interesting. I typically run Noise Xterminator first, then do a couple of other things, then run Blur Xterminator. I'll try it the other way around, makes sense to me.
Installing this broke my cuda acceleration, now my RC Astro tools have reverted back to running via the CPU
ouch!
@@DylanODonnell Probably a good idea to put up a disclaimer telling people it may break your CUDA acceleration
@@SimonT65 There is someone else in the comments where it worked and DeepSNR is GPU accelerated!
@@DylanODonnell I was using Russell Crowman's experimental PixInsight repository which bypassed having to install all the cuda toolkit etc. Maybe thats why it broke my cuda acceleration. Anyways, i've just spent 30 mins downloading and installing the full version as I couldn't get Russel's version to work again
all was going swimmingly until you mentioned it doesn't work for OSC ...........................!
Coming soon hopefully :)
In WBPP make sure you verify it recognized CFA images, then do 1x drizzle with drop shrink 0.6 to 0.9. Need to have enough dithering.
I’ve been using this tool almost since it came out, and there are tricks to get it working well every time. First you must dither, then your drop shrink size is paramount for this to work well. This depends a lot on your pixel scale and camera. In the DeepSkyCollective (I process a lot of images for the group) we use drop shrink of 0.35 and varshap 1.5. I found this works very well for my image scale (1.05) when I drizzle 2x. If I use the regular 0.9 square drizzle I get these speckles like you. But only at drizzle 2x at drizzle 1x they are gone… so it requires a little trial and error. There is also a trick to use this on single mono images that are not combined. Essentially you need to create 3 separate stack for that filter, combine in RGB, denoise then convert to greyscale. You shouldn’t have to reduce the size like you are doing to denoise using this… you really want to apply this early, just after deconvolution.. you should check Charles tutorial on this www.nightphotons.com/guides/single-channel-denoise you should also check the DSC suite which helps with creating triple stacks easily pixinsight.com/forum/index.php?threads/🌍-announcing-the-dsc-processing-suite-empowering-collaborative-projects-🌎.22833/
@steevebody449 great tips .. thank you!
Thanks Dylan.
Awesome info man.
Cheers man !
I was very happy photographing M83 with my 6" Newtonian and you ruined my night. Thanks but I didn't need to see that impressive image right now xD 🙈😅
I'm going to try it with Ha because I was doing RGB. Thanks for the idea
Greetings from Argentina
I think you could just use graxpert and move on with your day.
I get mixed results from graXpert .. probably me though!
No osc cameras, no independent interface ( you HAVE to have PI ), no gpu acceleration. For me that uses OSC camera, Siril and Affinity Photo sounds great! 😭
It's early days :)
the next update of siril will support deepsnr along with spcc iirc
@@vexari_ wow there you go !
have you tried graxpert?, it does background removal and denoise. I've used it with OSC data and other processing with siril and gimp. Also had the same issues with the spotty pixels when you run it on large image sizes so i'm not going to claim it's perfect. It is free though and runs independently so you don't need PI.