Written by Stylianos Spyrou
In this post, the concept of the hot pixels will be analyzed, the importance of removing the hot pixels from the FITS files will be emphasized and parts of the coding and the reasoning behind the steps followed will be explained.
What are the hot pixels and how are they obtained?
Hot pixels are single sharp pixels located at random locations of common images taken by digital cameras. They are points that do not react linearly to incident light captured by the lens. An important feature of the hot pixels is that they appear in the same location regardless the frame. This means they do not move, and they remain at a fixed position.
Hot pixels are caused due to electrical charges which appear into the sensor well of the camera’s lens. Since they are very sharp, and they are individual extremely bright pixels, they cannot be observed while looking at the image taken. However, they are very easy to determine while zooming at the images closely during processing, especially if the background of the image is very dark, such as the images taken from a telescope. They can also be visible when the sensor’s temperature increases or at very high ISOs. The weather conditions during the photoshoot also have impact on the existence of the hot pixels since, if the temperature of the surroundings is high, it is ideal for their formation of hot pixels on the lens during the shoot. Finally, they tend to appear far more often in long exposure images. The reasoning behind the formation of the hot pixels is that while capturing less light from the scenery in the given moment, the patterns obtained by the camera sensor are comparatively stronger in that specific moment. Lenses and camera sensors get hotter and hotter as they use long exposures.
Why & how to remove hot pixels?
It is very important to remove the hot pixels from an image. The main reason is that it affects the image significantly during close viewing or printing. The only way they can be removed is by following a processing method after the image is taken. This can either happen through photo editing or coding. In this particular article, the second method will be analyzed and explained in detail.
On Figure 1, the function that determines the hot pixels of each FITS file must be defined. In the first part of the code, the edges must be ignored, and they will be found separately later on. In order to understand the purpose behind it, we need to imagine the filter being a square with the center passing from every point of the image obtained. As the detector approaches the edges of the image, the corners of the square filter will exceed the limits and therefore the values they will obtain will be set by Python to zero, which affects the rest of the data (median/Gaussian filter).
As indicated in the Figure 2 above, the next step of the code is to find the pixels on the edges of the image, but not the corners. Repeat the process for the left and right edges, top and bottom.
The next step is to find the hot pixels of the image at its four corners. The code used is very similar to the one used to determine those at the edges and can be indicated in the Figure 3 below:
Using the previous Figures, the hot pixels can be obtained. Since the code would be required to be repeated for all images in order for them to get stacked, a part that repeats the following method can be introduced, which keeps the code simple and neat. However, the easiest method is to simply repeat the code for each FITS file of each cluster. A suggestion can be found below on Figure 4:
-  https://photographylife.com/what-is-iso-in-photography