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Image stacking and long exposure help


Lukeness
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I'd like to know what exactly long exposure does when using an SLR with a telescope. If im taking a picture of jupiter, does it increase its detail/size?

Also how does image stacking work? i know you take exposures of 5mins or something and multiple pictures, but what does stacking do?

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Long exposures, in a nutshell mean you can pull more light (photons) into your camea sensor and pick up more detail in deep space objects that you are imaging. These can then be stacked in a programme like Deep Space Stacker to "add up" all the data in the multiple images to give you a final more detailed image - after various processing techniques and tweaks are applied to it in something lIke Photoshop of the GIMP package. It is a bit more complex than that of course, but that is the gist of it. And a long exposure can be anything from 20 seconds up to 20 minutes and beyond depending on the kit you have at your disposal.

However, long exposures don't really work on planets - you are more likely to use a webcam/specliaised planetary camera to take a video of the planet and then "break" the video down into its components frames and stack them in a programme like Registax. Again that is a very basic interpretation.

Stacking, essentially, minimises the signal to noise ratio in your images and results in a cleaner, more detailed image than a single exposure.

If you are interested in taking up astrophotography, get holdof a copy of "Making Every Photon Count" - it's where I started and it will tell you everything you need to know to get cracking!

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Planets (especially Jupiter) are bright, so do not need long exposures - all you will do with a long exposure is saturate the sensor and end up with a bright white disk for an image. Marky is right, for Jupiter, you take a lot of short exposures and choose the best ones in order to catch the fleeting moments when the atmosphere is not messing up the view.

On the other hand, faint deep sky objects need long exposures to build up the number of photons on the sensor to distinguish them from the background noise. The longer the better for most objects, but in reality tracking, sensors noise and other factors limit the length of individual images, so multiple ones are taken and mathematically munged together in software to achieve similar (and often better) results.

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