Astro Pixel Processor

Combining subs with multiple exposure with APP

Viewing 4 posts - 1 through 4 (of 4 total)
  • Author
  • #15832

    posts: 1006

    For my own reference I asked @bula the best strategy for combining subs with multiple exposure times (with calibration files). The answer:

    There are several ways that you can do this and it all depends on what you are trying to achieve.

    If you still need to calibrate the data, then I would advise to calibrate both sets of data and save them in 2). If you have RGB data with chromatic aberration save them with the “align channels” mode, which reduces the amount of chromatic aberration significantly in most cases.

    Then proceed with your calibrated frames.

    You can play with the weights in 6) INTEGRATE

    • integrate with weights: equal, if you want all frames to be weighted equal, this will give you a result which will be subtoptimal in SNR, and suboptimal in sharpness
    • integrate with weights: exposure, if you want the longer exposure frames, which should have higher SNR, to have more weight. The integration should have better SNR but less sharpness
    • integrate with weights: quality, if you want to use APP’s quality calculation. The quality parameter is based on noise, stardensity, star size and shape. Usually this gives the best integration for noise and sharpness combined.
    • integrate with weights: SNR, if you want to use the SNR of the frames. This is a really dangerous method. Any deviating gradients between the frames will make the SNR metric totally unreliable. From all the settings, this is the least attractive one. I wouldn’t advise to use SNR for weights. Also bad frames with some clouds or bad transparancy will give higher SNR strongly reducing the integration result.
    • integrate with weights: noise, if you aim to have the lowest noise in the end result.
    • integrate with weights: star density, if you want to give more weight to the frames with the highest star density, this usually is a very good parameter to indicate good transparancy.
    • integrate with weights: star shape, if you want the frames with the smallest and roundest stars to have the most weight. This will give you the integration with the sharpest results. This works really well. Frames that have stars that are NOT round are punished a lot, so these frames will have little weight. Star shape means both roundness and size. The smaller and rounder the stars are, the higher the weight of that frame. This is a very nice integration setting if you have some frames without perfect guiding but still want those frames to help reduce the noise in the data.
    • Last option, you can make 2ย  integrations of the two datasets and combine them using the RGB Combine tool in which you have full control over how the images are combined. You will need to register both integrations first, before loading them into the RGB Combine tool.


    Scale Independent quality parameters in APP

    APP has the parameters star density & relative FWHM which are very helpfull if you combine data of different scales. APP calculates the star size/shape and star density relative to the scale differences between the frames. The scale differences are calculated using the homographies (projective transformations) between the frames.

    • 4 people like this.

    posts: 443

    With this kind of detailed information we can get the max out of APP, thanks for taking the time to describe and publish this info!!!

    • 2 people like this.

    posts: 642

    You are most welcome ๐Ÿ˜‰ ! Very vital question if you want to get the most optimal results from your data.

    If you are not sure which setting to use, use the

    6) Integrate weights: quality

    setting. This will give you a very nice balance for sharpness and noise in your integration ๐Ÿ˜‰

    • 1 person likes this.

    posts: 1138

    Excellent, maybe we can combine the previous posts and have a makeshift manual! ๐Ÿ™‚

Viewing 4 posts - 1 through 4 (of 4 total)

You need to log in or to reply to this topic.