Noise Sources | ||
|---|---|---|
|
Transition Distortion
: When an image is
electronically captured, it
is usually significantly
distorted. Different pictures
have different types of
distortion ("noise"). For
example, a picture that was
encoded into a television
signal such as
NTSC (National
Television Standards
Committee) is going to have a
different kind of noise than
a picture that comes from a
scanner. Pac-n-Zoom® is like a set of glasses for your computer. It can correct the digital picture by removing much of the distortion, but correct settings (like lens prescriptions) will be needed to get the best picture. In this paper, we will look at how noise gets into a picture and how Pac-n-Zoom can restore some of the original picture. Blurring is the worst noise in almost all digital images. It has two primary sources. | ||
| 1. | Transition Pixels: Let's
suppose a round dot is
printed on a piece of
paper as shown in the
"Transistion Distortion"
image. If we were to scan
the dot into the computer,
we might sample the dot as
the sample grid row shows.
Transition Distortion
The outside and middle
pixels are all white or
black respectively, but
there are two edge pixels
that are part white and
part black as shown in the
ratio grid row.When converted to gray scale in an array, we have several different ratios; so two colors (black and white) have been changed to black, white, and 3 shades of gray. Without perfect symetry, we could get 12 or more shades of gray. Pac-n-Zoom can "sweep" some of the gray out of the white and over to the black without changing the average color of the picture. Pac-n-Zoom can be set to restore the picture to the two original colors, but the average color will be changed slightly. | |
| 2. | Optical Aberrations: A very
small (about 1/4th of a
millionth of a square inch
per sensing cell or pixel)
optical array is used to
sample the dot. The
optical image cast upon
the array will add to the
transition pixels for
several reasons. Lets look
at two of the more common
problems. | |
| a. | Color: Lens are ground
to a specific
wavelength of light.
White is not a primary
color (it has a mix of
other wavelengths).
Therefore
chromatic abberrations
(distortions due to different wavelengths
of light) will occur. | |
| b. | Focus: A lens is only
focused perfectly at a specific
depth of field. In a scanner,
the optics can be set to minimized
this effect, but photographs often
have very big problems in this
area. | |
|
Since optical abberations blur the
image cast onto the sensing grid,
they cause the number of
transition pixels to magnified.
Pac-n-Zoom can be set to sweep
different amounts of transition
pixels. | ||
Color Flutter:Another type of noise (we will call flutter) multiplies the number of artifacts in a picture by creating slight changes in a specific color. Flutter can occur from electronic sources such as clock coupling, Johnson noise, dark current, beta mismatches, and a number of other ways. For example, flutter also occurs from a lack of homogeneity in the image light source.In another application, a digital speedometer has flutter when the car is going 54.5 miles per hour, and the speedometer vacillates between 54 and 55. To eliminate flutter, we could simply require a 2 mile per hour change before a new speed was displayed. This would be noticed on a speedometer, but it would not be noticed in a 24 bit continuous tone color picture. More than 90% of the people we tested could see the difference between 4,096 (4 bits per primary color with 3 primary colors) and 32,768 (5 bits) colors, but only about 18% of the people could see the difference between 32,768 and 262,144 (6 bits) colors. From these numbers, we can conclude 6 bits of color on 3 primary colors is probably enough. Pac-n-Zoom can be set to eliminate most flutter by requiring the color jump more than one level (7 bits of color are left). To prevent using resources on invisible color variations, the flutter setting is adjustable. Orphan Pixels:Another type of noise (we A picture's value is derived from the information in the picture. In other words, if no information can be extracted from the picture, it has very little value.To extract information from a picture, a group of pixels must be combined together into a constellation. Therefore a single pixel that can not be combined with any other pixel (an orphaned pixel) does not add value to a picture, and it should be eliminated. Orphan pixel can be caused by dust specs on the optics, dead pixels in the camera element, or by large electronic noise spikes. Small artifacts with high contrast are often a source of orphan pixels, but even in these cases, the orphan pixels usually detract from the picture. If the picture was painted on the computer by an artist, the artist might use the spray tool to create a shading and therefore orphans. The artist knows that your eye will average the orphan into the adjacent pixels. When Pac-n-Zoom eliminates the orphan, it averages it into the blob of an adjacent pixel. Therefore, the same artist created shading will still exist after the orphan elimination. All of Pac-n-Zoom's minimum artifact settings eliminate orphan pixels. | ||
Segmentation and Restoration | ||
|
Restoration
: Pac-n-Zoom®
can be set to eliminate
transition and
flutter noise,
and Pac-n-Zoom always eliminates
orphans by
averaging them into a
blob of
an adjacent
pixel. These are three common types of noises in digital images. By removing these three types of noise, the clarity, the contrast and the compressibility of the picture are all enhanced. Segmentation : Before intelligence can be extracted from a picture, a group of pixels have to be aggregated together and recognized by an intelligent extractor (usually a human being). When the picture is made more simple, it compresses better. Furthermore, it is usually more pleasing to the human being because the human being does not have to subconsciously aggregate artifacts that are inhibiting intelligent extraction. Pac-n-Zoom improves the picture appeal and compressibility by aggregrating the blobs; so the human does not have to work as hard. | ||