Stock: 8
In the Shadow of the Moon - 2024
How it Started
(Getting set up for the 2017 Total Eclipse)
The Capture
The Corona can only be observed in the narrow path of totality, the stretch of land that falls under the shadow of the Moon. I found myself in Western Ohio for this eclipse, as I was unable to make it to better weather in Maine after I had to completely change my plans away from Texas! The location had some high clouds, but luckily the data I collected was workable. Here's me setting up in a cornfield with the Askar 103, Redcat 61, and a sigma 135mm (not pictured). 
The photographic dynamic range of the Corona is somewhere on the order of 14 stops of dynamic range. This is impossible to photograph with a single exposure. This is THE hardest dynamic range problem in astrophotography. For this reason, we need to capture many bracketed exposures. This image comprises thirteen different exposure times from 1/1000s all the way to 4s long. Using SetNC, I was able to capture 15 of these brackets to make 15 HDR subframes to stack.
You heard me right! Due to the structure of my workflow, each bracket is composed as an HDR subframe to be stacked in the deep sky method, which I will detail later. The other critical thing of note here for the capture is ~calibration~. Calibration of TSE images must be perfect, just as in a deep sky image. For this image I shot around 200 flat frames, 300 bias frames, and 300 dark frames. The dark frames are matched to each of the 13 differing exposure times.
The Software
The challenges were much more complex than I initially thought. To solve these problems I had to educate myself up to the PhD level of image processing in order to understand the algorithm articles online. I wouldn’t be able to realize my vision until only last week, when I was able to solve the final challenges with properly captured images.
The goal of this software is to visualize the fine detail of the Corona. The Corona is the outermost layer of the Sun’s atmosphere, and it is composed of low-density superheated plasma, up to 1,000,000 degrees Celcius in temperature. The Corona is bent and twisted by the magnetic and radiative forces of the lower layers of the Sun. It is full of amazingly complex and intricate structures.
The problem is that these structures are very well hidden. They are very faint and low contrast, and along with this, they are hidden by the intense dynamic range of the Corona itself. The brightness change across the Corona is more than 14 stops of dynamic range! No camera can visualize this in one exposure time. In fact, the only thing that can visualize this is our own eyes, since our eyes are capable of handling immense dynamic range.
To overcome these issues, one must understand the application of these three algorithms:
Phase Correlation
The only algorithm suitable for aligning images to each other based on the corona is phase correlation. This is a highly sensitive frequency-based method for image alignment that is capable of using correlated image structures to align. It requires that one first hides the moving edge of the moon, bright stars, and the image edge itself. When all of these are done properly, this algorithm generates a bright peak in an empty image, who's position is equal to the pixel shift which matches two images!
Linear HDR Composition
Creating an artifact free image by hand blending images in photoshop is a near impossible task. In order to do this HDR blend properly, with calibration frames, registration, and all, we must do it linearly. That is to say with the data in its most raw form possible. By using a 'weight function', we can choose which pixels we want from each raw frame to compose the final HDR blend. We prefer properly exposed pixels, not too dark and not too bright, but in order for these to mix without artifacts, the images must be calibrated to each other so that all structures in the image have a coherent brightness. This way, the only thing that differentiates each image from one another is the noise level, and the overexposed regions. This way there are no artifacts, but in order to accomplish this you have to solve the mystery of how to properly match each exposure. To do this we use a linear fit function. Then we simply weight and sum all of the calibrated photos!
Adaptive Kernel Convolution
In order to sharpen our images, and remove the huge brightness gradient of the corona, we must use a high pass filter to isolate the highest spatial frequencies. There are many ways to go about this, but to tackle the issue in a way that preserves all the relevant details with minimal noise, the best way is adaptive kernel convolution. This is the formula we use to compute it. Basically, for every pixel in the image, you blur the image in a specific direction in order to best enhance detail and minimize the noise. We compute this filter for several different image scales to get a sharp final image.
The Print
This is a special image to me. It has taken thousands of hours and every ounce of my effort to create. It represents the absolute apex of my ability as an astrophotographer. So I want the release of the print to reflect these qualities inherent to the image. As such, they are printed on Hanmehule pearl paper, for its archival qualities, and for its beautiful representation of the tones and colors in the image. This is a museum quality print that should last a long long time!
Only ten prints are available for each size. These prints ship worldwide! They are signed and come with a certificate of authenticity for each edition. I hope you all enjoy this photo!
