Hi. Here is a reprocessed 5DMKII image using 1.3.5.281RC. Intentionally candy colours to highlight the variation in star colour. Many people spend time removing stars, but I love them. The image was also preprocessed in PI using a different technique, which I think has prevented the all to familiar data truncation experienced by DSLR users.
http://www.astrobin.com/full/41162/C/
Straight CIELab Luminance Retentiion
Straight CIELab Luminance Retentiion
Last edited by Rowland on Mon May 19, 2014 9:23 am, edited 1 time in total.
Re: Straight CIELab Luminance Retentiion - unmodded DSLR
With the DSOs nicely framed too!
You can also clearly see that, for example M8's core, despite being close to overexposed, still exhibits color that ties it in with the rest of the nebula.
And yes, good variation in star color.
What technique did you use in PI for the pre-processing? Can you give an example of the truncation problem?
You can also clearly see that, for example M8's core, despite being close to overexposed, still exhibits color that ties it in with the rest of the nebula.
And yes, good variation in star color.
What technique did you use in PI for the pre-processing? Can you give an example of the truncation problem?
Ivo Jager
StarTools creator and astronomy enthusiast
StarTools creator and astronomy enthusiast
Re: Straight CIELab Luminance Retentiion - unmodded DSLR
This is becoming something of a hot topic - rewriting.
Because my DSLR has very good temperature regulation and sub-frame consistency, I can dispense with dark optimization/scaling in PI. Furthermore, DSLR data is not particularly reliable because there is a degree of camera firmware generated non-linearity. I cannot speak for light frames, but I think linearity depends on the camera. It seems that bias and flats are near enough to linear.
Not related to PI in any way, DSLR bias subtraction may, in some cases, cause significant truncation of dark frame and subsequently truncation of light frame data. Bias only subtraction of lights, usually, does not truncate data, particularly if the bias is super-bias.
It seems that the best way to calibrate temperature regulated DSLR light frames is to leave the bias_in_the_dark (BITD). Bias frames are needed and used to calibrate the flats.
The upshot of all this is, bias only subtraction of light frames left line artifacts in low SNR regions, whereas, BITD removed line artifacts altogether, without data truncation and excellent removal of bad/hot pixels. Supercooled DSLRs -25C may not need darks at all, providing you are dithering.
Because my DSLR has very good temperature regulation and sub-frame consistency, I can dispense with dark optimization/scaling in PI. Furthermore, DSLR data is not particularly reliable because there is a degree of camera firmware generated non-linearity. I cannot speak for light frames, but I think linearity depends on the camera. It seems that bias and flats are near enough to linear.
Not related to PI in any way, DSLR bias subtraction may, in some cases, cause significant truncation of dark frame and subsequently truncation of light frame data. Bias only subtraction of lights, usually, does not truncate data, particularly if the bias is super-bias.
It seems that the best way to calibrate temperature regulated DSLR light frames is to leave the bias_in_the_dark (BITD). Bias frames are needed and used to calibrate the flats.
The upshot of all this is, bias only subtraction of light frames left line artifacts in low SNR regions, whereas, BITD removed line artifacts altogether, without data truncation and excellent removal of bad/hot pixels. Supercooled DSLRs -25C may not need darks at all, providing you are dithering.