Calculate single-frame SNR, stacked SNR, and optimal sub-exposure time based on Bortle class and camera noise parameters.
Enter your camera's read noise and dark current (from the manufacturer's sensor charts), pick your Bortle class, and set the target signal, single exposure length, and the number of frames you plan to capture.
Signal-to-noise ratio for one frame is the signal divided by the square root of all noise sources — signal, sky background, and dark current scaled by exposure time, plus read noise squared — and stacking N frames multiplies that SNR by √N.
The optimal sub-exposure marks where sky noise overtakes read noise; longer subs add little. Under a Bortle 1 sky (0.1 e⁻/s background) a 3.5 e⁻ read-noise camera reaches it near 123 seconds, while brighter skies cut it sharply.
It is the exposure length at which sky-background noise overtakes your camera's read noise, computed here from those two values. Beyond that point, longer individual subs add risk — satellite trails, guiding errors — without meaningfully improving the stacked result.
The calculator maps each class to a sky background flux, from 0.1 electrons per second per pixel at Bortle 1 up to 100 at Bortle 9. Brighter skies pile up noise faster, which lowers single-frame SNR and shortens the optimal sub-exposure.
Total signal divided by the square root of every noise contribution: target signal, sky background, and dark current — each scaled by exposure time — plus read noise squared. For a sky-limited frame, doubling the exposure time improves SNR by about √2.
Stacked SNR equals the single-frame SNR multiplied by the square root of the frame count, so 50 frames deliver just over 7 times the SNR of one frame. That is often the difference between a noise-dominated sub and a smooth final image.