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Messages - STEVE333

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General / Re: Starnet Problem
« on: 2019 September 30 19:37:44 »
i think you'd have to do that if it stops working again and will need to be done each time it stops working the first time after launching PI.


Thanks Rob. The funny thing is that when it didn't work and I closed PI then reopened it, loaded the same image, and then ran the Starnet process, it worked. I'll never understand computers.


General / Re: Starnet Problem
« on: 2019 September 30 17:42:28 »
In the PI Process Console, type:

Code: [Select]
cd /bin/PixInsight

Thanks for the response.

Since the Starnet process is now working should I still type the code into the Process Console?
Is this a one-time fix?


General / Re: Starnet Problem
« on: 2019 September 30 16:18:45 »
I saved the files, closed PI, restarted it, and, the problem went away. I was able to reload the image in question and run the Starnet Process on it successfully.

I feel a bit foolish, but, glad for the happy outcome.


General / Starnet Problem
« on: 2019 September 30 16:09:00 »
I've been using Starnet successfully as a PI Process for some time.

However, when trying to run it today (9/30/2019) I get the error message  "Checkpoint file not found!" and the process doesn't run.

Any ideas?


General / Re: Re-insert stars in starless image
« on: 2019 August 10 18:48:25 »
I also have had problems with large bright stars. One thing that has sometimes worked is:
  • Make a clone of your image
  • Run Starnet++ on clone to create the starless image
  • Use CloneStamp to cover the halos around large bright stars in starless image
  • Process starless image (sharpen, etc.)
  • Use max(starless, original)
This has often worked for me.


Just an update. I've installed Starnet++ into PI so that it shows up as one of the available Processes. Much easier to use, and, so far, it has accepted all images formats (including .xisf 32 bit). So, no longer necessary to save a 16 bit .TIF image in the starnet folder and then run Starnet++ from the Command Prompt window. Also, you keep all the precision of the original image.

Just FYI


Hi Bernd - With so many experts here on the forum I am a little anxious about commenting. However, here goes.

I too have a OSC but mine is a Canon DSLR (modified). I use a LED Lightbox as the extended source. I had the same problem you have with the different channels having significantly different signal levels.  In my case the Green and Blue channels had significantly higher signal than the Red channel. To balance this out I put a piece of Red cellophane (actually looked pink) between the lightbox and the telescope. This brought the Red channel significantly closer to the G/B channels and has worked well. The advantage of this approach is that (1) it improves the SNR for the Red channel, and, (2) I don't have  to worry about how to rescale the Red while properly maintaining any offsets at the correct level (a DSLR problem).

Even though you properly rescale the weaker channel(s), the weaker channel(s) will still have a lower SNR. That is the only point I wish to make. The colored cellophane helps overcome this problem.

Thanks for looking,


I downloaded your fit file and separated it into the R/G/B channels. The G and B channels look normal. However, there is definitely something wrong with the R channel, and, that is what is causing your image to be all greenish.


General / Re: Am I missing anything major from my workflow?
« on: 2019 July 24 22:02:32 »
Thank you for the feedback. You mention the burlap sack appearance. What really concerns me is something I have read on the internet about the sensor of the ASI 294 being defective. I am not sure that is the correct term,  but some have reported that if one extracts/ takes a picture of the sensor, and extracts the R channel, you can see if there is an issue with the sensor. Post # 12 here "take the red channel."  Do you know how to do that?

Thank you +filter

Not sure what camera you are using. Is it a OSC (like a DSLR) or are you capturing data through R/G/B filters?

If you are using a OSC then open the ChannelExtraction process. Drag the New Instance (triangle) icon from the process onto the color image. It will produce three grayscale images; one each for the R, G, and B images.


General / Re: Am I missing anything major from my workflow?
« on: 2019 July 24 13:33:03 »
Hi Nicholas - That is a very pretty image of the North America Nebula. For only 8 months you are doing well.

1) I noticed a fixed pattern noise that looked kind of like burlap sack across most of the image. Not sure what caused it. Possibly something in the calibration of the images.

2) BackgroundNeutralization (BN) is important to balance the background colors of your image to make true background "grayish". This is a necessary step for almost all images. This is done using a small Preview in your image where there is nothing but background (no target nebulosity).

3) ColorCalibration (CC) is very important, and, normally references the Preview used in BN.

4) HDRMultiscaleTransform is not always necessary, but, can be helpful to bring out details. The best Number of layers setting will vary from image to image, but, a setting of 5 or 6 would be more normal. Whether to choose To lightness and/or Lightness mask will also depend on the image (experiment).

5) CurvesTransformation is a stretching tool and is really not related to Flats. It can be used to "sharpen" an image when an S-curve is used (pull the curve down a little at about 1/4 of the horizontal scale and pul the curve up a little at about 3/4 of the horizontal scale) for the RGB/K setting. When the S setting is selected, raising the curve will increase the color saturation in your image which can greatly enhance an image.

6) Deconvolution can be tricky but useful. The link below is to a good tutorial on how to use Deconvolution.

7) I use LHE on almost every image I process. I usually apply a Luminance Mask to the image and then use LHE with a Kernel radius of about 26. I adjust the Amount to get the desired amount of detail sharpening. I then apply LHE again but this time with a Kernel radius of about 110. This helps to brighten larger area details in the image. Again I adjust the Amount to get the desired amount of enhancement.

You are definitely on a good path in your processing. I looked at you nice image on Astrobin.

There are a series of wonderful video tutorials at Harry's Astroshed. Each one is only about 5-10 minutes as I remember, and, only one topic is discussed, so, they are easy to follow, and free! I found them extremely useful when learning PI. Below is a link to the tutorials at Harry's website.

Hope this helps.


Hi J_N - As mentioned earlier you do have quite a bit of noise in this image. I too often have significant noise because of my location and the fact I can't always get as much data as I would like.

One thing I've noticed is that the more noise an image has the less the noise can be reduced. It sounds odd, but, since noise isn't eliminated but just reduced, when you have a lot of noise and reduce it too much the result is either a lumpy or "plasticised" background.

I usually use MultiscaleLinearTransform (with the Linear Mask active) to reduce the noise slightly while the data is still linear. Once the data is stretched I use TGV with the data protected with an inverted Luminance mask. Again the noise can't be reduced too far or you will get the undesirable artifacts mentioned earlier.

You may just be expecting the "Noise Reduction" to reduce the noise more than is reasonable for your data. I downloaded your RGB data and processed it using my normal process. I didn't include the Luminance data because I don't normally use Luminance. The results looked reasonable to me.

By the way, your stars all seem to have some "halos" around them. Don't know if this is a focus issue or high clouds or what.

Hope this helps. I can share my "typical" MLT and TGV starting values if you are interested.

I it's OK with you I can post your image with my processing so you can see the noise reduction I was able to implement.


Tutorials and Processing Examples / Re: MaskGen script
« on: 2019 July 04 09:29:48 »
In some cases, distortion can be a problem. When you see star centers not matching the mask, tweek your ImageSolver with higher magnitudes (i.e 14..17). This takes more time but should give you better results.

If you have doubts on non-masked stars, please verify the positions with Simbad and send me the coordinates.


Thanks Hartmut - And thank you for sharing all of your wonderful scripts. They make life so much easier!

If I find troublesome stars I will let you know. I will keep in mind your hint about using higher magnitude stars if distortion is a problem.


General / Re: Image processing help
« on: 2019 July 03 10:28:38 »
That is impressive .. especially from a reduced resolution jpg image!

The original RAW file is here if you want to play:

Thanks for sharing the data. I'll try processing it.


General / Re: Removing Noise from an Image
« on: 2019 July 03 10:25:47 »
Yes the uncalibrated light subs are mirrored after the meridian flip.

Hi Bob - I don't want to jump in the middle of this, but, after the meridian flip the light subs should be rotated 180 deg (not just flipped horizontally). Trying to calibrate subs that are just flipped horizontally will definitely introduce noise.

Have no idea what could cause this, so, that's it for me.


General / Re: Image processing help
« on: 2019 July 03 09:20:14 »
Yes please. For some reason, I just am missing how to adjust just that small band of brightness to pull out the Milky Way ... I thought it would be easy with curves/histogram, but it seems not.

I wasn't able to pull anything out of the clouds along the bottom portion of the sky. If I stretched that portion of the image it just got brighter and brighter. So, I used the GAME script to create a mask that just selected the clear portion of the sky and Milky Way above the clouds. I always blur the GAME mask to soften the edges so there isn't an abrupt transition in the processed image. Then I used:
HistogramTransformation to gently stretch the sky(and Milky Way).
CurvesTransformation to increase contrast.
LocalHistogramEqualization to further increase contrast (Kernel Radius = 110, Amount = 0.5).
CurvesTransformation to slightly increase the color saturation.
SCNR (Green, Average Neutral) to remove any unwanted Green.

The attachment below shows the result.

Thanks for letting me play with your image. Hope this helps.


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