What is the difference between bit depth and bitrate?

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What is the difference between bit depth and bitrate?

Understanding Bit Depth and Bitrate

When it comes to audio and video files, there are two terms that are often used interchangeably: bit depth and bitrate. However, they are not the same thing. Bit depth refers to the number of bits used to represent each sample in an audio or video file, while bitrate refers to the amount of data transmitted per second.
Bit depth determines the number of possible values for each sample in a digital audio or video file. For example, an 8-bit audio file can have 256 possible values per sample, while a 16-bit file can have 65,536. The higher the bit depth, the more accurate the representation of the original sound or image.

On the other hand, bitrate refers to the amount of data transmitted per second in a digital file. In other words, it’s the rate at which data is encoded in a file. Higher bitrates typically mean higher quality files with more information, but also larger file sizes.

Audio Bit Depth vs Bitrate

When it comes to audio files, the bit depth and bitrate are both important factors in determining the quality of the sound. A higher bit depth means a more accurate representation of the original sound, while a higher bitrate means more data is transmitted per second, resulting in a higher quality sound.
However, it’s important to note that a higher bitrate does not necessarily mean a higher quality sound. If the original recording is of poor quality, increasing the bitrate will not improve the sound. In fact, it can actually result in larger file sizes with no improvement in sound quality.

Video Bit Depth vs Bitrate

Video files also have bit depth and bitrate, but they work slightly differently than in audio files. Bit depth determines the number of colors that can be represented in a video file, while bitrate determines the amount of data transmitted per second.
A higher bit depth means a wider range of colors can be represented in the video, resulting in a more accurate and vibrant image. However, a higher bitrate is also important for video files, as it determines the amount of detail that can be captured in each frame.

It’s important to find the right balance between bit depth and bitrate for video files, as increasing one can have a negative impact on the other. For example, a high bit depth with a low bitrate can result in a choppy or pixelated image, while a low bit depth with a high bitrate can result in a washed-out or blurry image.

Final Words

In conclusion, bit depth and bitrate are both important factors to consider when working with audio and video files. While they may seem similar, they serve different purposes and have different effects on the quality of the final product. It’s important to find the right balance between the two to ensure the best possible sound or image quality.
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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.

Bit Depth explanation

Definition

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

Aspects to consider

The accuracy of each sample is determined by its bit depth. Then, the higher the bit depth, the higher the resolution in the digitized signal. In addition, the greater the bit depth, the greater the dynamic range for the signal because it will have more points to represent the amplitude of each audio sample. It follows that low levels of bit depth can affect the shape of the wave and thus not achieve a good representation of the original wave because there are fewer possible points to represent it. For example, in the following graph we can see a sinusoid represented with different bit depths. A depth of 1 bit will generate a wave more similar to the square wave (depending on the quantification) because we only have two possible points on the vertical axis.

Requirements

A very important aspect to keep in mind is that at greater bit depth we will 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:

Bit number * Sample rate * number of seconds duration [* 2 (if stereo signal)]

Then, for example, the size of a second of audio on a CD, which works with a depth of 16 bits and a sampling frequency of 44,100Hz / second will be given by the following account:

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

1 second = 1411200 bits (0.1764 Mb)

Sample Rate and Bit Depth

In sound and audio software and hardware specifications we are often told about processing capacities of up to 96kHz and 64bit operation, but what do these issues really mean? And how do they affect the quality of our sound?

Sample Rate and Frequency Range

The sampling rate is the frequency with which the A / D converter (analog to digital) measures the levels of a signal, the samples are broadly analogous to a series of snapshots. If the converter takes ten samples of the signal every second, it would have a sampling rate of 10 Hz.
The frequency range that an A / D converter (present on a sound card for example) can capture is determined by the sampling frequency, or sampling rate. However, in this there is a strict law that may seem unintuitive: the maximum frequency that can be captured is only half of the sampling frequency. A sampling rate of 10 Hz can capture a maximum frequency of 5 Hz, not 10 Hz. The reason is that, without double the samples of a sound source, some of the oscillations of the signal are lost.
But what happens if there are frequencies higher than the capacity of our sampling frequency in the captured analog audio signal? Aliasing then occurs, phenomena that occur when the highest sampling frequency that has been sampled is higher than the frequencies that can be accurately captured by the A / D converter. Aliasing adds distortion to the audio signal artificially, adding lower frequencies to higher partials. Aliasing can occur in a digital audio system as a result of a poorly designed A / D converter, but you are much more likely to hear it when you play high notes from a software-based synthesizer. If the synthesizer does not use an antialiasing technology, the high notes have the possibility of becoming random groups of tones that have no relation to the key note you are playing.

The researchers at Bell Laboratory are familiar with this problem since 1920 and conceptualized the principle as the Nyquist-Shannon sampling theorem. The theorem is simple: to sample the frequency value of x correctly, you need a sampling frequency of at least twice x. (The maximum frequency at which it can be sampled without aliasing at a certain sampling rate is thus the so-called Nyquist frequency.) So why do we need the sampling rate to be twice as fast as the most frequency? high to be recorded? Because each ordinary period of a waveform includes an upward and a downward oscillation. If the A / D converter takes less than two samples per period, it cannot capture the entire oscillation. In order to capture each “up” and “down” state, you need to take at least two samples from each period. Thus, the sampling rate has to be twice the highest frequency that must be recorded.

According to the Nyquist-Shannon theorem, to sample frequencies that are in the upper limit of the human ear (around 22000 Hz), you need a sampling frequency of around 44000 Hz, which is, not by chance, the rate Normal sampling for commercial audio CDs, 44100 Hz.

This obviously allows you to sample the frequencies from the top of the range of our ear, but what happens when the frequencies of the signal that reach the A / D converter exceed the maximum frequency limit of 22 kHz? They fold into the audible spectrum as distortion, so the A / D converters incorporate an anti-aliasing filter that eliminates these high partials, before the audio is converted to digital format.