Six processing option are available. The processing is applied in order from top to bottom. Only the processing options that are checked are applied.

  • Dark Subtract. A dark image is selected from the dark list, and the correction applied.
  • Bias Subtract. A bias image is selected from the dark list, and the correction applied.
  • Flat Subtract. A flat image is selected from the dark list, and the correction applied.
  • Flat Model Subtract.
  • AD Reduction. ADR is applied using the parameters determined during pre-processing.
  • Manual Alignment. Manual alignment is applied, using the parameters determined during pre-processing.
  • Negative Image. A negative image is computed.

 


Manual Image Alignment 

Manual image alignment is a two step process, and is done in the Pre-processing and Processing sections.

First the user picks alignment points in all the images, and this is done under the Pre-Processing tab. There are options to pick either a single alignment point or two alignment points.

The second step after picking the alignment points, is to align the images and this is done under the Processing tab. Manual Alignment is one of the check-able processing options. If only alignment is required, then only Manual Alignment checkbox should be checked. After alignment, the next step would be to stack all the aligned images, and this step proceeds automatically if the checkbox for stacking is checked (it is checked by default).

Alignment points would typically correspond to stars that can be easily identified on all images. After picking on a star, the actual point is automatically refined to find the central pixel of the star image. This auto-refinement will not work too well if the star is over-exposed and covers a large number of pixels, so it is best to choose stars that are bright and identifiable, but do not have overly large pixel presence on the image.

Using the terminology used below in the Auto-alignment section, the single point alignment is a translation transformation, while the two point alignment is a euclidean transformation.

As discussed further below, manual alignment is a good first step for EEC Auto-Alignment. If manual alignment is being done for this purpose, then it can be done fairly quickly since only an approximate alignment is required for ECC, which will fine-tune the alignment. Be sure to use TIF file format to preserve the image quality through several save and load steps.

 


Automatic Image Alignment

Alignment of images is required when the image moves across the field of view of the camera. For astronomical photos, there are 2 main ways this can happen.

  1. Camera on a fixed tripod taking short exposure photos that does not not track the stars.
  2. Camera that is guided to track the stars on an equatorial mount, but the tracking is not precise.

For the first situation, the images will contain translation and rotation effects. For the second situation, translation will be the dominant effect.

An additional effect that occurs is distortion from within the lens. Objects on the side of the field of view will move different distance across the image compared to those in the center of the field of view. This phenomena is most obvious in wide angle camera lens, but is still troublesome in longer focus lens such as 105mm and 200mm lens. It is less of a problem in telescopes, and probably negligible in most cases. This type of distortion complicates image alignment and requires "warping" of the images to make them overlay.

There are two auto-alignment methods available under the "Auto Align" tab.

 

Enhanced Correlation Coefficient maximization method (ECC method).

The ECC method has are four modes of operation:

  • Translation: An image is shifted (translated) in the x-axis and/or y-axis directions to obtain a second image. 
  • Euclidean: An image is a rotated and shifted to obtain the second image. When a square undergoes Euclidean transformation, the size does not change, parallel lines remain parallel, and right angles remain unchanged after transformation.
  • Affine: An affine transform is a combination of rotation, translation, scale, and shear. When a square undergoes an Affine transformation, parallel lines remain parallel, but lines meeting at right angles no longer remain orthogonal.
  • Homography: All the previous transforms are 2-D transforms. A homography transform can account for some 3D effects. A square when transformed using a Homography, it can change to any quadrilateral.

For photos taken with a regular un-guided camera lens, the lens distortion inherent in that lens will mean that both translation and euclidean transform are not the best options. For photos taken with a 105 mm lens, the Affine method seems to work best. ECC-Homography processing takes longer than the other 3 methods, and although gives good results, doesn't seem to offer any improvement over ECC-Affine.

There are 2 termination criteria for ECC. The Epsilon criteria is the probably the more important one, with default value at 10x E-5. Setting it too a smaller value (push the slider to the right) will make it work harder.

The threads slider for ECC specifies how many CPU threads will be used, and therefore how many images will be processed con-currently. Be careful pushing this to maximum, as it will use a lot of PC memory. On my PC with 32 Gb memory, the 4 thread option easily consumes 16 Gb of PC memory. So a PC with 16 Gb memory or less will struggle when using 4 threads. It's recommended to first do a test using several images and a single thread, whilst monitoring the PC memory, and determine what is best for your PC setup.

The threads option in the ECC processing is independent of the multi-threaded option that can be set in the Parameter menu, and ECC will always run as specified by the selection made here.

 

Akaze method.

This works by identifying key-points on each image. One image is assigned as the reference image to which all the other images will compared to. The key-points between each image and the reference image are matched, and transform computed to shift each of the images to overlay the reference image. 

The Akaze method imposes localized "warps" as required to make the images match. As such it can be considered to be able to apply more "severe" corrections, than can the ECC method.

There are a number of parameters for this method, but these are currently locked to values that seem to work best. A series of QC plots are generated during the processing showing the key-points, matching and an X and Y shift map.

The Akaze method works over a larger range of spatial movement between the images, than does the ECC method.

 

General Alignment Information

Both the Akaze and ECC require specification of a reference image. It is best that the reference image be an image that is in the middle of the motion of a series a images. This is particularly important for the ECC, which has a very limited spatial motion range over which the method is effective.

It is recommended to only use TIF format files. It can be seen that ECC reaches termination a lot quicker on TIF files, when compared to equivalent JPG files, implying the image degradation inherent in JPG compression is making the process more difficult. Note that TIF files derived from JPG files will have inherited the JPG degradation.

The best plan when using the ECC method, is to first perform manual alignment in the pre-processing / processing workflow (preferably 2-point, but 1-point should be OK). This will give images that are approximately aligned, but still with no distortion corrections imposed. Then run ECC on these pre-aligned images. The subsequent ECC will run quicker (ie, reach the termination criteria quicker) on these pre-aligned images, and all the images should be with-in it's narrower spatial operating range.

  


Stacking

Input data for stacking can come from either the image (loaded data), auto-aligned or processed file lists. Four stacking options are available.

  • Mean Stack. An average of all the checked image.
  • Median Stack (not yet operational).
  • Star-trail Stack. For making a single star-trail image from a sequence of short sequential exposures. See Star-trail stacking for some more details.
  • Plane Stack. For stacking images of planes taking off near an airport, with camera fixed on a tripod and a blue cloudless sky. See Plane stacking for some more details.

 


Multi-Threaded Processing 

The default processing option is to do all processing sequentially in a single CPU thread.

Some of the processing methods have been optimized to run multi-threaded. The multi-threaded option will be used if the this option is allowed in the Parameters menu. The multi-threaded version will run quicker than the default single thread.

Ssupport for utilizing Nvidia GPU graphics cards has been investigated as an option for speeding up the processing. Although this has been demonstrated to work well for some processing options on an Nvidia GTX 960 card, this option has not yet been made available due to the complexities in making the libraries for distribution and the very large size of the resulting distribution package.