Interlacing and channel bandwidth

[ppppenguin]

For stationary pictures, as Opcom has explained, interlace does halve the bandwidth needed for a given resolution and refresh rate*. For moving pictures it's more complex. Yes, there is better temporal resolution for moving objects, though vertical resolution in those objects is reduced. Also when you try to de-interlace the picture, as required for LCD panels etc, you soon find out that it's not easy to do well.

It is now simple to do the TV equivalent of multiblade shutters as used in movie projectors. Framestores were a long way in the future in the 1930s

*It's not exactly half. There are additional artefacts caused by interlace that give a lower perceived vertical resolution than you might expect. The Kell factor is used to quantify this.

[old_tv_nut]

Originally Posted by ppppenguin

...*It's not exactly half. There are additional artefacts caused by interlace that give a lower perceived vertical resolution than you might expect. The Kell factor is used to quantify this.

The "Kell Factor" relates to having scan lines (sampling in the vertical direction); there is an additional degradation if the lines are interlaced. But since all widely used TV standards were interlaced, the term Kell factor was applied to the net effect in interlaced pictures. This is taken to be roughly 0.7. This is a subjectively determined number and not a law of nature, and can vary greatly depending on the brightness of the picture, the viewing distance, the contrast of the test pattern details, and the refresh rate.

When non-interlaced sampling was considered (the horizontal pixel sampling in digital versions of 525- and 625-line systems, or vertical resolution of a progressively scanned system), a higher factor could be applied. For the hroizontal sampling, SMPTE and ITU standardized on filters that are 3 dB down at 0.85 of the Nyquist rate. With these specs, the system was judged to be transparent to the analog signal. The limiting resoluton is probably about 0.9 of Nyquist.

[ppppenguin]

AFAIK there's nothing very scientific about the Kell factor. As oldtvnut says, it's determined subjectively without a great deal of theoretical backup. My feeling FWIW, is that it depends significantly on the vertical scanning aperture. In tube cameras this is gaussian which gives a falling vertical spatial frequency response. Usually corrected, at least partially by vertical aperture correction. Like wise in CRT receivers but without VAK. LCD displays and CCD cameras have a very different vertical aperture, much squarer.

The Kell factor has been used to justify decisions about choosing H bandwidth wrt number of lines. Has any good experimental work been done with modern cameras and displays? In any case all HD systems we use square pixels so if there is still a Kell effect there is a shortfall of vertical resolution.

[old_tv_nut]

Originally Posted by ppppenguin

...In any case all HD systems we use square pixels so if there is still a Kell effect there is a shortfall of vertical resolution.

Not sure what you mean here. "Square pixels" is a lousy term, as it does not refer to the display elements having a certain shape. This phrase is used to mean that the centers of the pixels have the same spacing vertically and horizontally. Pixels are point values of color and do not have shape or dimensions.

If you mean the display elements have square shapes, then, yes, this implies a certain vertical and horizontal spatial frequency response, different from that with a Gaussian CRT spot.

[ppppenguin]

Originally Posted by old_tv_nut

Not sure what you mean here. "Square pixels" is a lousy term.....

This is a commonplace term to indicate that the pixel spacing is equal on H and V axes. By contrast to SD digital systems where the spacing is not equal.

As oldtvnut correctly points out, in all sampling theory the idealised sample is infinitesimal in length. (Dirac delta function if anyone is that interested). In TV this is generalised to 2 dimensions rather than one. Practical pixels have a finite size and shape. For LCD displays and CCD cameras this ideally approaches a square having the same dimensions as the pixel spacing. This gives a zero order hold function and hence a loss of HF response on both axes which follows a sin(x)/x curve.

The point I am trying to make is that the assumptions which underpin Kell Factor stem from the days when H scanning was a continuous function while vertical scan was sampled. These assumptions may well not apply when the picture is inherently sampled at the sensor on both axes. As a thought experiment consider a sensor and/or display where each pixel can be individually addressed. They can then be read or written in an arbitrary sequence*. I can conceive that this might affect motion protrayal (motion above a very slow rate is aliased in TV systems) but I cannot see how it might affect our perception of H and V resolution. Hence the Kell factor of a progressively scanned system using modern techniques should be unity.

I may have overlooked something here. For example unless there is some kind of optical filter before the sensor there can be H and V aliasing. Or there may be performance problems of the sensor that affect the axes differently.

*In doing this thought experiment I was influenced by BBC Research Report 1991/4 "Image Scanning using a Fractal Curve" by John Drewery. http://www.bbc.co.uk/rd/publications..._1991_04.shtml John Drewery had a superb understanding of scanning, sampling and spectra. Back in about 1975 I remember him demonstrating the 3 dimensional spectrum of TV signals (PAL in this case) using some wonderful models that he had the BBC Research Dept workshop make from pieces of coloured PTFE. Nowadays this would have been done by computer graphics.

[old_tv_nut]

Originally Posted by ppppenguin

...Hence the Kell factor of a progressively scanned system using modern techniques should be unity.

I may have overlooked something here. For example unless there is some kind of optical filter before the sensor there can be H and V aliasing. ...


*In doing this thought experiment I was influenced by BBC Research Report 1991/4 "Image Scanning using a Fractal Curve" by John Drewery. http://www.bbc.co.uk/rd/publications..._1991_04.shtml John Drewery had a superb understanding of scanning, sampling and spectra. Back in about 1975 I remember him demonstrating the 3 dimensional spectrum of TV signals (PAL in this case) using some wonderful models that he had the BBC Research Dept workshop make from pieces of coloured PTFE. Nowadays this would have been done by computer graphics.

The Kell factor relates to how close to unity you can come, even with progressive scan. You can't get unity because the phase of sampling is restricted to the positions of the sampling points. That is, if the details lie exactly on the sampling points, you get full amplitude, but if they lie halfway between sampling pints, you get zero amplitude. The sampling becomes equivalent to a synchronous detector. So, the Kell factor says how close you can come to unity and still perceive a repetitive pattern correctly given that the filtering in the system consists of the sensor spot or element shape, the display spot or element shape, and the human eye optical function. Interlace makes it worse, but it's not unity for progressive.

For a full explanation of 3-dimensional spectra resulting from scanning, I also recommend an out-of-print book by Pearson:
http://www.amazon.com/Transmission-D...n+transmission

[ppppenguin]

Originally Posted by old_tv_nut

You can't get unity because the phase of sampling is restricted to the positions of the sampling points. You can't get unity because the phase of sampling is restricted to the positions of the sampling points. That is, if the details lie exactly on the sampling points, you get full amplitude, but if they lie halfway between sampling pints, you get zero amplitude.

This would apply equally to both X and Y axes on a sampled system, so resolution is degraded euqally on both axes. It is also a misunderstanding of sampling theory. This works equally well in space as well as time. If you sample a signal using infinitesimal size samples at more than the Nyquist limit the original signal can be reconstructed exactly. This is also applicable to 2 dimensional sampling, as noted by Mertz and Gray in their famous 1934 paper. If the sampling aperture is finite you get a falling frequency response, the exact response depending on the shape of the sample aperture. For example a square aperture competely filling the sample pitch would give a sin(x)/x response with a little over 2dB drop as you approach the Nyquist limit. In the real world it is difficult to put a sharp cutoff optical filter ahead of the sensor so there will be aliasing. This suggests using a sensor with more pixels than needed for your TV system and filtering the output. This is equivalent to using oversampling ADCs. It is also one reason why some of the best SD pictures are obtained by downsampling an HD input.