Masked integration?

[mperron]

Hello,

I've been playing with some of my images and got to wondering...

Lets say I have 50 hours worth of Lum for a target...say M51. If I integrate all 50 hours I get excellent signal to noise, but poor resolution. If I only take all images with a FWHM = 1.5" or less I get great resolution but poor(er) signal to noise for the faint stuff.

Would there be any worth/way,  to use the high resolution data for all the stars and structural regions of the image which would benefit from resolution (which also appear to have reasonable signal to noise anyways) and combine it with the high signal to noise image to bring out all the really faint things such as tidal streams or IFN which may not benefit from such high resolution. This would make use of many of the images that never seem to pass the grade and get discarded anyways.

I'm not sure if smoothing routines would be just as effective...but it's just a thought.

Mike

[RickS]

I have attempted this a couple of times with a degree of success, doing two integrations with one weighted to best FWHM and one for best SNR.  Then I used PixelMath to blend the dim parts of the best SNR integration with the bright part of the best FWHM integration.  It took a bit of messing around but did produce a good result.  I haven't done it often enough to try to reduce it to a simple recipe.  Maybe I'll give it a go and document it next time I have some data worth the effort...

Cheers,
Rick.

[avandonk]

Why not use HDRComposition with your high resolution image as the 'dimmer' one. It can be made 'dimmer' with pixel math. HDRComposition uses a mask to replace saturated stars in the 'bright' image with star data from the dim image. This mask is controllable with a slider. Bert