



|
I've been using Nebulosity 2 for primary image processing
for a few years now and found it to be a powerful and inexpensive
tool to capture and process astro-images.
(To see some of my images click on
the Gallery link on the left) Nebulosity is the
brain child of Craig Stark and can be purchased on his web site
http://www.stark-labs.com/purchasing.html. Craig has versions for
Windows and MAC computers.
I have found that collecting the images is the
easy part. However, processing the images to bring out the details and
color of the object and reduce the noise is quite a bit more
challenging.
To help others that might be interested
and to park the info where I can find it easily, I thought that I
would put some processing notes on my site. Some are excerpts from
the Nebulosity user guide.
The basic steps in order are as follows:
- Decide on how you’ll deal with hot pixels (Bad Pixel Map
vs. Dark subtraction)
- Prepare sets of darks, flats or
bias frames to remove hot pixels, vignetting, etc.
- Batch Preprocess B&W/RAW images
using the darks & flats from above. I have been using the simple
dark subtraction method and select auto scale the darks.
Now you'll have a set of images named "pproc_OriginalImage.fit"
- Convert RAW images into color via Demosaic
(if one-shot CCD used and captured in
RAW, which you really should do) and square-up your pixels (if
needed)
- Pull down Batch, Batch Demosaic +
Square (if images are from a one-shot color camera)
or Batch Square (if images are from a monochrome camera or you
just feel like squaring
up a color cam's but keeping the image as monochrome for some
reason).
- Select your frames
- Ideally, Nebulosity will start loading
and reconstructing the frames. If it pops up a dialog
asking for things like offsets, it means it did not recognize
what camera captured the
image (or you have “manually override color reconstruction”
checked in the Preferences).
If this happens, consult the Reconstruction: Demosaic’ing and
Pixel Squaring section in the manual.
- In the end, you'll have a set of images
named "recon_pproc_OriginalImage.fit"
- Grading and Removing Frames. I use the
Grade image Quality option in the batch mode. Then I look at
the lower quality images and see if they should be removed
from the stack using the Preview image option. At this point you'll have a set of
images named "Qnnn_recon_pproc_OriginalImage.fit
- Match Histogram using Highest Quality frame
( the one with the lowest Q number) as master.
- Pull down Batch, Match Histograms
- Select a reference frame and press OK. This
will serve as the template image that others will be
matched to.
- Select the set of frames you wish to normalize
- In the end, you'll have a set of images named "histm_Qnnn_recon_pproc_OriginalName.fit"
- Stack the images (Align and Combine) Don't
use Auto Align if you have stars for alignment points. I use Drizzle
2X and Atomizer set to 3.
This is slower but more accurate.
- Crop the image to clean it up - Make sure
that you crop off the edge of your image,
removing any shaded area due to image shift prior to using the AUTO
COLOR BALANCE
- (color only) Remove skyglow hue - Auto
Color balance
- Stretch the image (Levels, DDP, etc)
I've been experimenting with the Digital Data Processing (DDP)
option and found it works well on some images. However for most of
the images I use Levels and Curves. I also increase the color by upping
the Saturation some. Usually I start with 50% and see how
it looks. One of the final things I do is reduce the noise using the
GREYCstoration Noise Reduction function followed by the
Tighten Star Edges tool. I usually use the default value of 1.0
- Once the Image is to my liking I save it as
a FIT as well as a JPEG.
Since Nebulosity lacks the filter and layer functions that are found
in Photoshop, I typically import the JPEG into PS and do some
final tweaking there.
At the present I only have PS6 which processes image in 8 bit
color depth only so I keep the processing to a minimum.
The complete Nebulosity 2.3 user manual (PDF)
can be found HERE
(Continue Page 2) |
     
Help Support this site. Check out the Google ads
below!
|