Noise Reduction - Important Concepts in Signal Processing, Image Processing and Data Compression - page 17

used prior to applying DNR to prevent DNR from causing the other noise reduction
system to mistrack.
One of DNR's first widespread applications was in the GM Delco Bose car stereo
systems in U.S. GM cars (later added to Delco-manufactured car stereos in GM vehicles
as well), introduced in 1984. It was also used in factory car stereos in Jeep vehicles in the
1980s, such as the Cherokee XJ. Today, DNR, DNL, and similar systems are most
commonly encountered as a noise reduction system in microphone systems.
Other approaches
A second class of algorithms work in the time-frequency domain using some linear or
non-linear filters that have local characteristics and are often called time-frequency
filters. Noise can therefore be also removed by use of spectral editing tools, which work
in this time-frequency domain, allowing local modifications without affecting nearby
signal energy. This can be done manually by using the mouse with a pen that has a
defined time-frequency shape. This is done much like in a paint program drawing
pictures. Another way is to define a dynamic threshold for filtering noise, that is derived
from the local signal, again with respect to a local time-frequency region. Everything
below the threshold will be filtered, everything above the threshold, like partials of a
voice or "wanted noise", will be untouched. The region is typically defined by the
location of the signal Instantaneous Frequency, as most of the signal energy to be
preserved is concentrated about it.
Modern digital sound (and picture) recordings no longer need to worry about tape hiss so
analog style noise reduction systems are not necessary. However, an interesting twist is
that dither systems actually add noise to a signal to improve its quality.
In images
Images taken with both digital cameras and conventional film cameras will pick up noise
from a variety of sources. Many further uses of these images require that the noise will be
(partially) removed - for aesthetic purposes as in artistic work or marketing, or for
practical purposes such as computer vision.
Types
In salt and pepper noise (sparse light and dark disturbances), pixels in the image are very
different in color or intensity from their surrounding pixels; the defining characteristic is
that the value of a noisy pixel bears no relation to the color of surrounding pixels.
Generally this type of noise will only affect a small number of image pixels. When
viewed, the image contains dark and white dots, hence the term salt and pepper noise.
Typical sources include flecks of dust inside the camera and overheated or faulty CCD
elements.