Advanced Digital Video (Part 1)

Welcome everyone to “Introduction to digital video concepts”, as part of our QSC Quantum Training,

an advanced service and troubleshooting curriculum.

My name is Patrick Heyn and I’ll be giving you a brief introduction

to some of our more advanced video topics as they relate to NV Series video end points.

If this is your first experience with Q-SYS Video,

we highly recommend that you START with our Q-SYS Video 101 online training.

This should give you a good baseline on the NV Series’ functionality before we dive into deep-geek stuff.

Speaking of which, let’s get start with a discussion of video color, shall we?

RGB or Red, Green and Blue color model is the most commonly used today

because it mostly closely models the human eye

and it also best represents the actual pixel data on video display devices.

The human eye contains rods, that detect the light intensity and cones, that perceive color.

Each pixel contains a subpixel

usually an RGB element which are controlled to display a desired color and light intensity.

The RGB color model can be mathematically mapped and transformed into something called a Color space.

Color space defines the maximum and all allowable color on a given device.

The complete subset of colors within a color space is defined as its color gamut.

Many of these standards you see on the left here, define more than just the mapping function,

color space and color model, as they can also define dynamic range, resolutions, frame rates, bit depths, etc.

Speaking of which, the color bit depth is the number of bits that define a single color of a pixel.

The color precision portion of the video can be defined as bits per pixel or per color.

With 8, 10 or 12 bit color, it is defined as bits per color not per pixel.

The complete range is called Full range color and 16 – 235 is called Limited range color.

Typically SMPTE/CE rates support a Limited color range and IT/VESA rates support a Full color range.

Now don’t get color space confused with color encoding.

Color encoding systems are defined as sets of rules that are used to encode RGB data

into a more easy-to-use form that can be transmitted using less bandwidth.

Using the YCbCr encoding system the Luma (Y) is the brightness portion of the image,

sometimes referred to as the black and white or monochromatic portion of the image.

Chroma (C) is the color portion of the image.

Transforming an RGB signal into the luma and chrominance components has many useful properties.

RGB signals carry redundant data,

one reason being that the luminance is being carried over all three RGB components.

Transforming to YCbCr is performable via a mathematical transform

which is 100% recoverable when transforming back to RGB.

Digital subsampling is frequently used when transmitting and or saving digital data.

The human visual system is much more sensitive to brightness than it is to color.

When a video signal is separated into the luma and chrominance components,

the luma portion can be transmitted via high resolution bandwidth.

However, the chrominance portion can be subsampled to reduce bandwidth requirements.

This image shows the chroma was significantly compressed but the luma remains uncompressed.

The subsampling process is expressed by a 3 or a 4 (4 parts if alpha channel is included).

These subsampling ratios are used to create a conceptual bitmap J pixels wide and 2 pixels high.

Ratios use arbitrary variables J:a:b which are:

J= the sample space for the conceptual bitmap

a = the number of unique samples in the first row

b = the number of unique samples in the between the first and second row

The resultant bitmap is not an actual representation of how many pixels are displayed on a device.

Instead, this just gives us the representation of how many color samples are transmitted per pixel

and can be used to calculate the amount of bandwidth reduction.

For example, 4:4:4 means 4 samples.

4 Unique samples in the first row and 4 unique samples between the first and second row.

4:2:2 means you still got 4 samples.

2 Unique samples in the first row and 2 unique samples between the first and the second row.

But this does provide a bandwidth reduction by 1/3

Here are the supported color formats, RGB which is always 4:4:4: and YCbCr 444 and 422.

And that's pretty much the baseline vocabulary on color.

Let’s take a quick break now and dive into some more Ancillary video data when you get back