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IMAGE SENSORS, PIXEL SIZE, AND POISSON NOISE (continued)
2. WHAT IS 'NOISE' IN PICTURES?
PHOTOGRAPH | DARK PORTIONS | GRAINYNESS | PIXEL LIGHTNESS ERROR
I'd like to show you a PHOTOGRAPHic image of some bridge near Bergen (Norway), a picture that was taken in August 2005:
fig.2-a: Bridge Photograph
Impressive subject, though obviously underexposed.
I used an inexpensive "digital" snapshot camera; I suspect exposure control was misled by these very light areas in the sky.
Now I magnify that portion of the image that surrounds the left pillar of the bridge.
fig.2-b: Area near Left Pillar Magnified
Here you see an effect well-known to everybody who magnifies "electronic" PHOTOGRAPHs: The pictures contain quite a coarse GRAINYNESS; much coarser than the pixel size itself would allow.
The "grains" can generally be described as PIXEL LIGHTNESS ERRORs which are distributed at random all over the picture. This "random" or haphazard property made scientists call it "noise".
Is it really haphazard? -
I admit that I was dissappointed. I searched quite a lot of photographs for real "random" noise ... and didn't find one.
Whether snapshot or artefact from the lab: either there is no discernable noise or the noise contains traces of periodic structures and of image processing artefacts. And: it's very difficult (or impossible at all) to find pictures that contain clean noise from just one source.
So I cannot show you an image with clean Poisson noise.
But in the next paragraph, we're going to take a closer look at the most important different sources of noise in pictures.
For the sake of faster download times, I used compressed JPEG image file formats for the above illustrations. Of course they contain JPEG-artefacts.
If you want to check the more exact uncompressed <*.bmp>-files, please feel free to use my image directory.
Continued: 3. NOISE COMPONENTS
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Last modified July 3rd, 2006