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Identifying Andromeda galaxy in an iPhone photo with SkyChart

Posted 4 years ago

POSTED BY: David Ameneyro
8 Replies

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POSTED BY: EDITORIAL BOARD

Hi David,

You can certainly get a long way with cellphone photographs these days. Especially wide-field astrophotos like this. Your raw DNG file has all the required information. To bring out some of the detail you need to adjust some of the parameters that influence the histogram of intensity values.

You may want to start by seeing what exactly you can import from your DNG file:

Import["andromeda-raw-original.DNG", "Elements"]

This will give you a list of all the available import elements for this particular file.

{"BitDepth", "CameraTopOrientation", "Channels", "ColorProfileData", "ColorSpace", 
"Data", "DateTime", "EmbeddedThumbnail", "Exif", "FilterPattern", "FlashUsed", 
"GeoPosition", "GPSDateTime", "Graphics", "Image", "ImageSize", "MakerNote", 
"MetaInformation", "RawData", "RawExif", "RawImage", "RedEyeCorrection", 
"Summary", "Thumbnail"}

Lots of metadata! Of these, you might like to try

Import["andromeda-raw-original.DNG", "Summary"]

for a brief summary of primary properties of the image, or you can retrieve any specific properties using

Import["andromeda-raw-original.DNG", {{"DateTime", "GeoPosition"}}]

(Be aware that your GPS location when you took the photo is embedded in the file...)

To get the image we can use

dng = Import["andromeda-raw-original.DNG", "Image"];

The dimensions of the image are

ImageDimensions[dng]
{3024, 4032}

so we see that this is the full 12MP image (3024 x 4032 pixels).

The Mathematica function ImageAdjust will be useful to shift the histogram of intensity values. Here is the histogram using the null (no adjustment) ImageAdjust parameters, {0,0,1}:

ImageHistogram[ImageAdjust[dng, {0, 0, 1}]]

When you run this you will see that most of the image intensity values are less than 0.1 (as you might expect in a mostly black image). We can use a very rough adjustment in order to see some detail. (You will notice that your histogram shows three colours (RGB, in this case) because this DNG has three channels - try ImageChannels[dng] - the adjustments below may also be applied separately for the different channels.)

So, we'd like to do two things: increase the brightness of the image (basically multiply each pixel intensity value), and adjust the contrast (primarily to shift the blackpoint of this image - although there are other ways to achieve this too).

Firstly, lets just brighten the image:

ImageHistogram[ImageAdjust[dng, {0, 6, 1}]]

You will notice that the histogram is now 'fuller'. Values that ended up larger than 1 are clipped to 1. If you look at the image that this adjustment generates

ImageAdjust[dng, {0, 6, 1}]

you will notice two background features quite easily: the halo in the lower third, and the cloudy glow in the upper third. The halo is an artefact of the image. I'd guess that the sun had just set (~6pm on December 21st) in Seattle, with atmospherically diffracted light possibly causing this optical effect. Other sources are nearby streetlights, etc. Tricky to remove this though without interfering with the neat actual astronomical feature that you captured in the upper third: the Milky Way! (One way to avoid having sun-related optical effects is to take the images well after twilight has ended.)

We can shift the "blackpoint" of the image in a number of ways (to darken the background sky i.e. reduce sensor noise). One possible way is to introduce a contrast adjustment (the first value in the ImageAdjust parameter list):

ImageHistogram[ImageAdjust[dng, {1.5, 6, 1}]]

or even with a bit of gamma correction

ImageHistogram[ImageAdjust[dng, {1.5, 6, 1.01}]]

The diffraction halo is still very clear, but the Milky Way is now a little clearer too.

You can read more on the parameters in ImageAdjust here.

Using a combination of functions you can get rid of the halo, but it unfortunately also removes the background Milky Way. For example,

ImageSubtract[dng, 0.03] // ImageAdjust;
processed=ImageAdjust[%, {.4, 4, 1.04}]

will give you a pretty good wide-field view of the stars in your image. (ImageSubtract has been used here to roughly adjust the blackpoint.)

And for the portion that involves Andromeda,

ImageTake[processed, {2050, 2640}, {660, 1350}]

gives enter image description here

POSTED BY: Mark Dowdeswell

Hi David,

This is really interesting! One function you might consider for image analysis projects like these is MorphologicalComponents, which will let you take your binarized image and extract all kinds of measurements from those points of interest. I think that you'll find it very fun to play with!

POSTED BY: Arben Kalziqi
Posted 4 years ago

Thanks for the tip @Arben K ! I will check it out on some of the photos from my most recent shoot

POSTED BY: David Ameneyro

Awesome; excited to see how it turns out! (I should also add that ComponentMeasurements is what you'll be wanting to look at explicitly...)

POSTED BY: Arben Kalziqi
Posted 4 years ago

Hey I've been told that my published notebook can't be downloaded due to size.

If you want original-size photos and full notebook try this OneDrive link (you should be able to open in browser without needing an app or sign-in):

https://1drv.ms/u/s!Ar9wm50Mtk3Tgckd6wK18du6xTLooA?e=89QmPD

POSTED BY: David Ameneyro

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POSTED BY: EDITORIAL BOARD
Posted 4 years ago

I had to use really low quality pics to get this under the 20MB file size limit. Check out full size pics here: https://www.wolframcloud.com/env/ameneyro/Published/andromeda-writeup-v2.nb

POSTED BY: David Ameneyro
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