This question may seem vague, but I'm far from an expert at photography/photometry/etc, so please bear with me...
But, let's say for instance I wanted to compare two images of the sun from differing telescopes-- inherently causing the image sensors/ccd/software to likely be different. Thus comparison of images takes place at the RGB 1024x1024x3 3-dimensional matrix level through MATLAB, a matrix-based language.
Since, for instance, I can retrieve digital images from different observatories that represent nearly the same image when analyzed qualitatively, where do the cmos/ccd/photon sensors cause differences at-- if any at all? As the sun is so large in size and the observatories are viewing relatively the same side/angle of the sun, what hardware/software differences would cause thus matrices to differ?
Here's what I've thought of so far; some inferences and some researched:
- The demosaicing algorithms may differ across units.
- Since all cameras have a sensor noise that is related to the type of camera it is and this can be used to identify the type of camera that took the image--as discussed on How can I tell if two pictures were taken with the same camera without metadata? --then differing sensors should cause differing noise values and thus differing RGB matrice values.
- The file format and data transfer from each telescope may differ, causing data loss, and maybe other issues. But a consistent raw format(or file format in general) may combat this, or so I assume.
- Since MATLAB converts these images to the aforementioned matrices, then do these conversions invoke other issues as this isn't the native means of image representation on a computer?
Much appreciation for the long, very detailed answer from @jrista
I'm sorry for the confusion, but I'm not hoping to identify the type of camera based upon their noise, metadata headers, or anything of the sort, but rather the relatability amongst differing cameras on different telescopes, hoping that there is, in fact, a standardization of equipment as there is for image file format.
Anyways to elucidate on what I'm hoping to do and why I'm wondering such a question, I will further explain what I'm hoping to find out and why a somewhat "standardized" camera--containing data values that are relatively similar--is something I require. I don't mean to be too detailed or require answers for my project; I just think the confusion will persist without an in-depth explanation as to why I want to know such things.
I will be taking in FITS data from many ground-based solar observatories as well as FITS data from many space-based solar observatories. In doing so, I hope to use image differencing techniques--subtracting the space-based solar observatories' image from the ground-based one--yielding some RGB matrice values. The images will, in fact, be from the same time frame and I will be using a computer algorithm to determine the displacement/misalignment of the images, as the alignment of the two images is imperative to the success of my research. I will also be experimenting with a normalization function I wrote and other averaging and collectively image processing techniques I find useful to ultimately find a consistency amongst these values regardless of the telescopes in which such data was collected. Astronomical seeing distortions cause many problems with ground-based observations and I hope to quantify such seeing distortions through their pixelation values yielded via the differencing. I understand astronomical seeing, have taken into account the many variables that can AND will come up, and so I don't need an explanation as to why this will fail unless you're absolutely sure due to some fact about cameras/sensors and how their images will inherently cause some difference that I'm ignorant too. I've created plans to combat such variables.
All in all, my question as concise as possible--
Will differing cameras' images(at the pixelation value) be inherently different regardless of if the image is the exact same object?