Newsgroup: it.media.video.produzione
Titolo: (Inglese) (Lungo) Risoluzione CCD e oversampling conversion

Allego qui, anche se lungo e in inglese, un articolo tratto dal sito
Microsoft relativo al TV broadcasting, in cui si parla chiaramente
e in modo serio della tecnica usata per l'oversampling, cioè la
tecnica di digitalizzazione dell'immagine ottica così come avviene nei
moderni CCD delle telecamere.
Da questo articolo si può comprendere chiaramente il metodo usato
per scannerare una immagine ottica con tre CCD da milioni di
pixel, non necessariamente 720x576, ed avere maggiore risoluzione
finale.
Questo non lo faccio per buttare un sasso in piccionaia, ma per far
capire ai numerosi adepti delle note leggende metropolitane ( "nel
CCD delle telecamere tutto ciò che è superiore a 720 x 576 pixel
non serve a niente, al massimo serve per lo stabilizzatore o per
le foto") come vanno in realtà le cose del mondo reale, non
in quello di 
videoin.org
.
Purtroppo è lungo, si perde un po' sui discorsi dell'aliasing,
 e vi perdete le immagini dei diagrammi
che sono esplicativi, ma tant'è.
Eccolo, nei suoi passi più signifiicativi:
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Whilst we can't improve the shape of optical filters and we can't change the
 physics of the aperture effect, we can, however, change the frequencies
at which the effects occur. A 576 active line camera can't give 576 lines of
resolution, but a camera having more lines can.
Effectively, the camera is using oversampling.
Figure 4 shows that in an oversampling camera, the spatial sampling rate
must be increased by using a larger number of pixels in both dimensions.
 In this example, the factor is two although other factors are possible.
The optical anti-aliasing filter then only needs to prevent aliasing at the
twice the original sampling rate. Although the optical filter has a gradual
cut-off slope, we are only interested in the bottom half of the band, where
 the response is reasonably uniform.
The output of the CCD element is digitized and fed to a signal processor
designed to act as a spatial low-pass filter having a response shown in
Figure 4. This cuts off at half the original sampling rate, thus allowing
that rate to be halved without aliasing. The television industry calls this
a
downconverter. In computer terminology it's a resizer. The result is a
TV signal with the target pixel count. It will contain no spatial aliasing,
but will not suffer loss at the band edge.
The reason oversampling works is that real sensors and displays
have aperture effect, whereas a pixel represented by a binary number
doesn't. The sensor and display need more sampling sites to handle
all of the information in a pixel array. It is quite possible to have a
series
of pixels at the Nyquist frequency, even though no camera or display
could resolve it directly.
Another way of looking at oversampling is that the ideal anti-aliasing
 filter would be digital, but the Catch-22 is that you can't use a digital
 filter until after the sampling stage and then it's too late.
In oversampling, the sampling rate is temporarily raised to allow a
realizable
 optical filter to be used prior to digitizing.
Once in the digital domain, the real anti-aliasing process
is in a digital filter where the bandwidth and sampling rate are defined.
Note that we can only avoid spatial aliasing using a interlaced scan sensor.
 An interlaced sensor has half the vertical sampling rate in each field and
when
the fields de-correlate due to motion, vertical detail suffers spatial
aliasing.
A downconverter needs to be motion vector steered so that detail from
two fields can still be combined in the presence of motion.
In addition to extracting the maximum resolution at the sensor,
oversampling should also be used at the display to render the
 raster invisible. Once more, a form of resizer is required,
but this now increases the number of lines using interpolation.
As before, the process is much easier to implement and works
better with scanned input signals because they are separable.
Raising the number of sampling sites describing the picture puts a gap
in the spectrum as shown in Figure 5a. Instead of an impossible
steep-cut filter, a realizable filter with a gentler slope in Figure 5b
 is perfectly adequate to eliminate the sampling sidebands.
     Figure 5b)
      Gentle filter can remove Sideband without affecting Baseband
The aperture effect of the display can be turned to advantage
to filter out the raster, leaving the passband unaffected.
Figure 5c shows the signal displayed conventionally on a
CRT with the separate intensity functions of each line making the raster
visible.
 Figure 5d shows the result with oversampling.
The intensity functions overlap and the depth of modulation due to the
raster falls.
The same technique is used to transfer digitally manipulated images
back onto movie film without the any visible raster.
     Figure 5c)
      Conventional CRT has deep raster modulation
     Figure 5Oversampling CRT gives reduced depth of raster modulation
      Oversampling maximizes resolution of CRT whilst minimizing visibility
of raster
The number of lines needed in the channel between is then quite moderate.
Progressively scanned sensors and displays having 700 to 1000 lines
connected by a 720 bit channel are all that is required to deliver a truly
high definition television service. Oversampling makes the transmission
inherently scalable because the upconverter in the display is optional
and lower cost receivers could omit it.
Large expensive receivers would use upconversion to recover
all of the resolution in the transmitted signal and suppress the raster.
These could also incorporate motion vector steered frame rate
upconversion to reduce background strobing.
Figure 6 contrasts the traditional and oversampled
approaches to transmitting a television picture.
If we began with a 4x3 aspect ratio standard definition progressively
 scanned digital picture having square pixels, it would contain something
like
 704x528 = 371,712 pixels.
In an interlaced system we discard every other line to create a field.
This results in 720x288 = 207,360 pixels, halving the required bandwidth.
Using oversampling, we pass the entire picture through a downconverter
that reduces the sampling rate in both axes by the square root of 2 or 1.41.
The output picture will then be 720x576 = 414,720 pixels, also halving
the required bandwidth. The downconverted picture simply removes
the bandwidth that is not explored in real cameras because of aperture
effect.
In other words, the downconversion is effectively lossless.
When the oversampled picture is to be displayed, it is simply upconverted
 to, say, 996x746 pixels and displayed with no visible raster, no spatial
aliasing,
excellent dynamic resolution and no half frame rate components.
Essentially oversampling is a near-lossless or artifact-free way of
halving the bit rate from a sensor. Interlace is an inferior way of halving
the bit rate,
which results in a high level of artifacts and damages dynamic resolution.
In an MPEG environment, the downconverted progressive scan pictures
are easier to compress than the interlaced scan pictures for various
reasons.
Firstly, in an interlaced picture, the macroblocks cover twice the screen
area
so motion compensation is more approximate. The motion compensation is
further degraded in interlace because the vertical aliasing confuses the
motion estimator.
Consequently, although the input bit rates in our example are the same, an
MPEG compressor could achieve a lower output bit rate on the progressive
picture than on the interlaced picture for the same level of compression
artifacts.
The figures here are simply examples, but the principle holds at any picture
size,
allowing commercially available equipment to be used. Using oversampling,
million pixel cameras and displays connected by a  channel give extremely
 good results.

che sono esplicativi, ma tant'č.
L'articolo non č reperibile in rete?
Grazie 
	Augusto