Calibrating Images:
Since dark and bias noise is not random and is consistent from image to image, techniques have been developed to allow scientific and technical imagers to remove these sources of noise from their images. This process is called "calibrating" the image. Dealing with both dark and bias noise involves making two special images and subtracting them from the photo. The first image is a bias frame - a zero-duration exposure in which the sensor is reset and immediately read out, without any light falling on the sensor and with no time gap between the reset and readout. The image that this process creates is a snapshot of what the sensor's bias noise looks like, since the only contribution to the resulting image is the readout amplifier's static.
The other special image is the dark frame. This is most commonly an exposure of the same duration, taken at the same sensor temperature, as the photo. Since no light is allowed to fall on the sensor, the resulting image shows only an accumulation of dark noise (plus bias noise - since to get the image you have to read out the sensor). For various reasons, in most scientific imagery the bias and dark frames are generated as separate steps and subtracted from the photo separately, in a defined sequence.
However, most digital cameras do not allow a zero-duration exposure without the use of special software - such as testing software used by camera service departments, or expensive software written specifically for science and engineering applications, which might require that physical modifications be made to the camera to operate properly. For this reason, most photographers who are calibrating their digital SLR images are doing so with a single combined bias and dark frame, taken as an exposure at the same ISO, shutter duration, and ambient temperature as the photograph.