1. How big are the noise
elements? If
you were to look at the above squares from across the room, they
probably all look dead equal. Up close, you probably can spot
the one with the 3% noise quite easily. I certainly can on my
laptop.
So one factor
of noise is this: How big are the chunks that contribute to it?
Big chunks = Bad. Small chunks = Good. If each pixel is a noise
element, you can get away with a lot. After all, that 3% patch
is noisy 1 part in 33.3, but they're distributed in single pixel
sized differences.
2. Corollary
to this is how
big is the whole image reproduced? If you shoot a noisy image and shrink
it down to Internet scale, the down-sampling of the noise averages
it out with its neighbors, to a marked degree, especially if
the noise is comprised of single pixel differences (it isn't
always).
Want proof?
Of course you do. Here are two images. Both shot with the "noisy"
828, but each is a cropped slice from a 816 pixel wide reduction
(25% of original). One was shot at ISO 800, the other at ISO
64. Which is which?
Answer at the bottom
of the article.
If you printed
the full image as a 5x7 print, you would see minimal noise, depending
on the subject. But the detail and color would be great.
3. Some of noise depends
on its point of reference. Copy
each of the three patches above onto a single graphic layout
and print them on the world's finest printer with the world's
finest glossy paper and most sparklingly perfect ink and tell
me if you can spot the difference.
You probably
will see LESS of a distinction between them on a print than you
see here on your computer screen. But then, there are computer
screens that have a somewhat random noise to their phosphors
or LCD elements, and those could mask the look of the gray squares,
too.
4. Some of noise depends
on its local environment. Detail
masks noise. You can detect noise in broad areas of continuous
tonality much easier than you can in areas of strong small-scale
tonal variation.
Blue skies
are continuous, grass and foliage is not. Man made graphics are
often noise-revealing due to smooth tones of paint or color while
images of the Grand Canyon on a clear day may hide noise among
the rocks and strata. Out of focus backgrounds will reveal it
while your portrait subject's hair will tend to hide it.
5. Some of noise's impact
on an image depends on the relationship between the noise and
the eye of the beholder. If you can see it and it is disruptive, it's too
much. But if it isn't disruptive, your eye may treat it as some
other characteristic.
The world
of photography is filled with examples of "noisy" images
shot backstage, under a street lamp, deep undersea, of a beautiful
nude, in available light or of a graphically strong subject that
carry the impression of Gritty Documentary, Interesting Texture,
or Graphic Counterpoint instead of simply "noisy image".
6. Some of noise's impact
depends on how much camera sharpening is present. Punch the image up into
the Sharpening + zone, and up goes the noise. Dial in Sharpening
- and down it comes. To a degree.
When shooting
images at smaller file sizes, the down-sampling idea (Item 2
above) improves detail while tending to blend small scale noise.
Lifting the Sharpening setting tends to not recover noise as
much. You can get away with less in-camera digital sharpening
on smaller files.
7. Some of noise is perceived
through chrominance.
Black and white images get away with more than color images do.
Take a picture with noise in it and drain the color out of the
shot so the tonalities are what your eye is responding to and
the monochrome image will tend to look like high speed film instead
of a noisy color shot. Of course color film gets noisier the
higher its ISO goes, but B&W is more forgiving.
So, how
does the chip performance of the V1 compare to the 828?
The 828 has
an image size advantage over any 5-megapixel image. It's 27.5%
wider than the V1's array of pixels, so shooting an image that
puts the same subject onto the same number of pixels is not an
exact science. But that is what has to be done to make a direct
pixel for pixel comparison of the two cameras.
I managed
to do it, fairly closely, but not exactly. Still you can see
several interesting things in these two examples. What you see
here are 100% crops right out of the center of a string of tripod
shots that were made a few minutes apart of the same subject.
Notice the shadow wander between each series.
If the display
on your monitor is a typical 90 ppi, the V1 image would be 28.8
inches wide! And the 828 image would be 36.3 inches wide!
The V1 is
on the left. (If these show upon your browser screen one above
the other, widen the window till they fit side by side.
They're QuickTime
animations, so you can stop their motion by clicking the lower
left animation box to pause it. Then you can move the time button
back and forth to access the ISO frame you wish to compare to
its neighbor.
