In digital imaging applications, noise is commonly assumed to be bad, a characteristic that makes images worse. Although many types of noise are known, their origin and, more importantly, their impact on images is often misunderstood.

One way to judge noise is to view images. For example, Figure 1 shows two monochrome images with gray levels that appear similar. Although these images look the same, when a section of each is enlarged, there is an obvious difference between the two (Figure 2). Because the image on the right clearly shows significant graininess — a visible consequence of noise — one would think that the camera that took the right-hand image had more noise...