bit depth vs bit rate Archives - Page 2 of 2

The difference between 16 and 24 bit depth

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Analog / Digital Conversion

When you record a guitar into digital audio, the guitar’s analog signal is converted to digital signal for storage on your computer.

Since the analog signal can take an infinite number of values while computers have limited capacity, it is sampled according to two parameters:

Sample Rate: This is the number of times per second when measuring an analog signal (often we are at 44,100 Hz, or 44,100 times per second)
Resolution: defines the number of possible values that the measured value can take and is measured in bits.
If its resolution is 1 bit, only two values are possible: 0 and 1.

For each added resolution bit, the number of possible values is multiplied by two:

2 bits = 4 values
3 bits = 8 values
16 bits = 65,536 values
24 bits = 16,777,216 values!
During recording, therefore, we will measure the incoming signal many times per second and complete this measurement according to the number of possible values.

Hypothetical example: Our resolution means that we can only store values equal to 0 or 1. If the analog input signal is measured at 0.8, it will be rounded to 1. If it is measured at 0.2, then it will be rounded to 0.

Very simple, right?

As a result, the higher the resolution, the closer the recorded signal will be to the original signal. This is what you see in the following image:

Effect of different bit resolutions on sampling precision

Also, one might think that 24-bit recording provides better quality than 16-bit. In fact, the resolution seems more accurate and the final signal more realistic.

However, this is not really what it should look like …

A history of noise

Previously, we saw that the values measured from the original signal were rounded off during analog-to-digital conversion.

If we rebuild the signal to listen to it again once the values have been rounded, we will notice that it is slightly different from the initial signal.

Quantization errors when sampling an audio sample

This phenomenon is called quantification error and it is inevitable.

If we isolate this error, we realize that it is actually noise, which is added to the signal.

If you increase the resolution (English bit depth) by adding precision bits, the error will be less, and therefore the noise will be less.

More precisely, for each bit added, the noise level is reduced by approximately -6 decibels (noise level = noise level).

In other words, for every 1 bit of resolution added, the dynamic range over which a signal can be correctly recorded increases by 6 dB.

Therefore, we deduce the following figures:

16 bit = 16 x 6 = 96 dB dynamic range
24 bit = 24 x 6 = 144 dB dynamic range
In the end, the only difference between 16 and 24 bits lies in the noise level. And therefore, in the dynamic range available for recording, “above” the noise level.

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Bit depth, an important factor almost unknown

Very often we see people talking about topics that are important, like bitrate for example. Most of the time without understanding exactly what that means. Sometimes they even do trial and error and for various reasons it may be that the result they obtain is misleading, since they are not considering that modifying the bitrate without looking at the sample rate and the bit depth, is to act blindly and therefore the Results will always be misleading and we should not draw definitive conclusions from them.

We have detected that many people instead of giving a reading that allows them to understand what bitrate, sample rate or bit depth are, prefer to manipulate them without understanding them and, based on the result of one or two songs, they often reach conclusions. wrong about what is the right combination.

Bitrate

It is bitrate It is the amount of information that passes per second, that is, the amount of detail that an audio file can contain in a video. The bigger the bitrate means what will be passing more information per second; therefore the file will be bigger but it will contain more details, which will give it a higher quality. We will put an example to understand it very easily. Images that we have a great draftsman or painter and that we ask him to make a portrait of a person but we tell him that I can only use 5 colors and he cannot mix them.

As a result we will obtain practically a caricature and not a portrait itself. In other words, it will have less quality if we understand quality to be a faithful copy of the original.+

On the other hand, if that same painter asks you to make a portrait, but we stop using the entire color palette, you will be able to make a very realistic portrait, of very high quality, very faithful to the original.

Why did this happen? Because it contains much more information. There are many more shades. That explains exactly how bitrate affects the quality of a video or audio file.

Sample rate

When we record a video, for example, it is as if we were taking a series of photographs and then quickly saw them one after the other and that would give us the illusion of movement. In exactly the same way that cartoons worked in ancient times. Obviously if we only use three drawings per second the quality of the cartoon will be very low because you will see a series of jumps and not an action continues. If instead we use 24 drawings per second we will see a very high quality cartoon where we will seem to see an action continue without any Jump.

The sample rate is the number of samples per second that are taken to form a video or an audio file. Audio on a professional CD uses 44100 samples per second. If we lower that quantity we will notice a loss of quality and if we increase it to more than 44100 samples we will be able to obtain a very high quality HD.

Bit depth

The bit depth determines how many “steps” the curve or wave will contain that will contain our audio or video file. Obviously, the more steps the wave pattern has, it will be more faithful and, on the contrary, if it contains few steps, the wave pattern will be very rough.

So here we are understanding the importance of bit depth that for example in music affects even the dynamics of music. That is, how much can the volume of an instrument rise and fall in different passages. At different bit depth rates we will obtain different levels of decibels

Bit depth: definition

In digital audio, the bit depth is the number of bits of information in each sample and is closely linked to the resolution of the audio. Unlike an analog signal, which is periodic and is made up of infinite points, digital audio is a discrete signal since it is made up of a finite number of points. Use binary numbers (bits) to determine the number of states available to represent the strength of each audio sample and thus represent the signal. “The quality of the representation generally increases as this number of states increases. For example, […] recording of high-fidelity music is obtained on a CD with 65,536 levels of amplitude. The number of possible states of an n-digit (n-bit) binary system is E = 2 ^ n. ” 1. In summary, it is the resolution, in terms of amplitude, that a digitized signal will have. Determine the dynamic range that said signal has. In the following image we can see how a signal is represented in 4-bit depth. 4 bits generate 16 possible values on the vertical axis.

Requirements

A very important aspect to keep in mind is that at a greater bit depth we are going to need more resources to process the audio and more memory to save it. This is because we will have more information. The size of our audio file will be given by the following account:

Number of bits * Sample rate * number of seconds in duration [* 2 (if it is a stereo signal)]

So, for example, the size of a second of audio on a CD, which works with a depth of 16 bits and a sampling rate of 44,100Hz / second is going to be given by the following account:

1 second = 16 * 44100 * 2 (since it is stereo)

1 second = 1411200 bits (0.1764 Mb)

Comparing different bit depths

In the following table we can compare the dynamic range (in decibels) and the number of possible amplitude values of a digitized signal with different bit depths.

Obviously, the higher the number of bits, the higher the states are possible. The following example compares two pieces of music, leading them to a 16-bit to 4-bit transition. The first piece works in more depth, and the transition is much more noticeable, the result in 4-bits is perceived as the effect of “aliasing”. In the second piece, less dynamic range is used, so the transition it undergoes is almost imperceptible to the ear.