Continuum Subtraction in Astro Photos

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  • Опубликовано: 8 сен 2024

Комментарии • 12

  • @tostativerdk
    @tostativerdk 4 месяца назад +1

    Great explanation, thanks for the video :)

  • @cratervanawesome
    @cratervanawesome 3 месяца назад +1

    Thank you for explaining this like I'm 5. I have been seeing a few videos about this process in my feed over the last bit, but didn't fully understand the use case for it.

  • @jtepsr
    @jtepsr 4 месяца назад +2

    As always craig, wonderful demo

  • @RigoFromSpain
    @RigoFromSpain 4 месяца назад +2

    super demo Craig, love it

  • @rocketcityastro
    @rocketcityastro Месяц назад +1

    great video i don't use PS and likely never will but i got the idea and im sure i can do some fancy pixel math to accomplish the same thing.

  • @bottaripaolo
    @bottaripaolo 4 месяца назад +2

    wow... beautiful!!! 😮👏👏👏

  • @fishrmn703
    @fishrmn703 Месяц назад

    Craig, is the red continuum layer just a copy of the master red from WBPP?

  • @DSOImager
    @DSOImager 4 месяца назад +2

    Nice demo of this technique. I use pixel math in pixinsight to perform these steps but I can see where this works out better in certain situation.. especially the nebula shots like M78. Thanks for sharing.

    • @markpetersen2130
      @markpetersen2130 4 месяца назад

      Do you use the NBColourmapper script in PI? I’ve gone back and forth with doing CS in linear mode in PI vs stretched mode in PS and I’m liking the PS method for its ability to quickly dial in just the right amount of blending.

    • @DSOImager
      @DSOImager 4 месяца назад +1

      @@markpetersen2130 I'm not using the NBColourmapper script. I have found that I like the results of combining SHO data while linear. Sometimes I'll do a linear fit with Oiii as the reference before combining. For HaLRGB or even HaOiiiLRGB I've been using the continuum subtraction method with pixel math. After watching this video.. It looks like following this technique in PS might be better for certain types of images.