Hi All -
Because of my light pollution and limited imaging time I always have plenty of noise in my stacked images. Recently I have been successfully using a new technique to reduce the noise in the stacked image. It may be a known technique, but, I haven't seen it before.
The link below takes you to a tutorial showing how to use the technique. I've found that it takes about 2 to 3 minutes to perform the noise reduction.
https://theskysearchers.com/viewtopic.php?f=22&t=5799
After viewing the tutorial the following may help to explain how the noise reduction is achieved. The technique reduces the noise by averaging each pixel with it's four nearest neighbors (one at a time) and then averaging those four averages. It reduces noise by almost a factor of 2 while retaining all the pixels (no binning). It does slightly blur the image (very slightly) which is the tradeoff to reduce the noise (no free lunch as they say).
The equation below shows the four individual averages, and, then their average to produce the desired result. It is the averaging of noise from adjacent pixels (not the blurring) that leads to the noise reduction.
[(orig + R)/2 + (orig + L)/2 + (orig + U)/2 + (orig + D)/2] / 4 = Average
Comments welcomed.
Steve
Because of my light pollution and limited imaging time I always have plenty of noise in my stacked images. Recently I have been successfully using a new technique to reduce the noise in the stacked image. It may be a known technique, but, I haven't seen it before.
The link below takes you to a tutorial showing how to use the technique. I've found that it takes about 2 to 3 minutes to perform the noise reduction.
https://theskysearchers.com/viewtopic.php?f=22&t=5799
After viewing the tutorial the following may help to explain how the noise reduction is achieved. The technique reduces the noise by averaging each pixel with it's four nearest neighbors (one at a time) and then averaging those four averages. It reduces noise by almost a factor of 2 while retaining all the pixels (no binning). It does slightly blur the image (very slightly) which is the tradeoff to reduce the noise (no free lunch as they say).
The equation below shows the four individual averages, and, then their average to produce the desired result. It is the averaging of noise from adjacent pixels (not the blurring) that leads to the noise reduction.
[(orig + R)/2 + (orig + L)/2 + (orig + U)/2 + (orig + D)/2] / 4 = Average
Comments welcomed.
Steve