Sensitivity
ISO: International Standards Organization
ASA: American Standards Association
ISO
and ASA
are essentially the same thing - it is an agreed upon value for the sensitivity
of film or imaging surface. This allows us, for a given scene, to use
the consistent shutter/aperture combinations regardless of the imager
type.
Electronic devices all have an optimal level where
they function the most efficiently. Amplification above this baseline
value decreases the signal-to-noise ratio. In digital photography this
noise shows up as "grain." The more a weak signal is
amplified, the more difficult it becomes to distinguish actual information
from background noise - the image becomes "grainy."
The image to the right is a 100% crop. Pixels are depicted in a
1:1 ratio - each sensor pixel is represented by a single pixel in the
image (with the appropriate Bayer interpolation). This view allows
us to analyze noise patterns with excruciating exactness.
If the image were resized, noise characteristics
change due to the averaging and interpolation that occurs with resizing.
Resizing down decreases visible noise by averaging noise out with neighboring
pixels. Upscaling an image will distribute the noise pattern as the
pixels themselves become bigger and interpolated (combined) with neighboring
pixel information.
This crop contains 1/10th of the actual image map.
It is an ideal size as it is easily transmitted over the internet and
allows for side-by-side comparisons. We can use this technique to
visually see the difference between sensor performance characteristics.
The above image was taken at ISO 200. Move the mouse
cursor to see the same image taken at ISO 1600. Click on the image
to see a side-by-side comparison.
Noise reduction techniques are available, but tend
to confuse high frequency data (read: detail) for background noise. The
net result is noise reduction robs detail from images.
As stated earlier, CMOS sensors are inherently noisier
than CCD sensors. Manufacturers combat this with different approaches. Canon, for example, applies noise reduction algorithms to the data coming
off the sensor before it is actually recorded. Kodak, simply records all
of the data, including noise, and deals with it using software.
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