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Data compression techniques

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It is evident that coding techniques for multimedia information contain large amounts of data that require memory space for recording and high transmission speed for transfer to other digital systems.

These needs can be met by reducing the space occupied by the data with special compression techniques. Compressed data cannot be used directly for processing, viewing, or playback. Compression techniques are used by special programs immediately before data storage or transmission. During the read or receive phase, similar programs perform decompression. Compression can be done on the basis that information encoding techniques dedicate an always equal amount of memory to each information element (be it a character, a pixel or a sound sample), regardless of their statistical frequency and its significance.

The compression techniques developed so far are more than a hundred but grouped into two categories:

Compression without loss of information.

Lossless compression techniques are based on compact coding of the same data streams or coding with a small number of bits of the most statistically frequent data.

This compression is completely reversible and the decompression program returns the exact bit sequence as it originally was. For this reason, loss-free technique is applicable to any type of data, including executable texts and programs, although the achievable compression factor is not very high: values usually range from 2: 1 to 4: 1. Of course, these results vary depending on the type of input data.

RLE encoding

The RLE (Run Length Encoding) compression technique is oriented to equal byte sequences. In the original version, it provides the introduction of a special character that indicates the beginning of a sequence, and instead of encoding the same characters in the sequence one by one, it encodes only the first one, followed by a number indicating where many times drawn and repeated. Specifies with the Sc character at the beginning of the sequence, the statement

these ******** are eight stars… these Sc * 8 are eight stars

where 8 is not encoded as an ASCII character but as a binary number.

The decompression program interprets the next byte as a counter and rebuilds the original sequence.

For image compression, RLE encoding only works well with images that contain large areas of uniform color, but are not very effective with complex images.

Compression with loss of information.

Loss-free compression techniques are not sufficient to solve the problem of the huge amount of data generated by encoding multimedia information, e.g. Video images while allowing better use of memory space on disks or data transmission lines. High resolution. , audio or video.

However, to try to solve this problem, it is necessary to remember that multimedia information, although subject to transformation, can remain understandable; This allows for compression factors that are higher in some orders of magnitude than those observed.

These interventions can be studied based on the behavior (vision and hearing) of our sensory systems to reduce the required memory without obvious changes in information content. Compression techniques that do this are called “lossy” since the least significant piece of information is irreversibly suppressed. Therefore, it appears that the bitstream after decompression is different from the original, and therefore these techniques cannot be used for other types of information, e.g. Text. Furthermore, the information thus compressed is not suitable for further processing as the loss introduced with each subsequent step becomes more and more apparent.

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What is video encoding and how does it work?

The technique of compressing videos

What do we mean when we talk about video coding or, as industry experts generally call it, video coding?

Simply put, video encoding is the process of compressing and converting video content. The ultimate goal is to use less storage space, use less bandwidth, and make the user experience smoother. It goes without saying that the compression process causes a significant loss of information. The more data that is applied, the more data is deleted in the video. The result is a different version of the original due to missing data.

Why is video coding so important?

Video encoding is essential for transmission because it simplifies the transmission of video on the Internet through a compression process. Compression reduces the bandwidth required while providing a high quality experience. Without this, raw video content would not allow many users to view content on the Internet due to insufficient connection speeds. The protagonist of this process is the bit rate or the speed of digital data transmission that can be transmitted in a certain time interval in a communication channel. When streaming, the bit rate determines whether users can easily view the content or are exposed to video buffering.

Another fundamental aspect of video coding is compatibility. Indeed, sometimes the content is already compressed to an appropriate size, but it still needs to be encoded to be compatible with different devices and applications, although this is often referred to as transcoding.

The video encoding process is governed by video codecs, which are compression standards that are created through software or hardware applications. Each codec consists of an encoder for compressing the video and a decoder for restoring an approximation of the video for playback. The name codec is actually derived from the merging of the words “encoder” and “decoder”.

But what is the best codec?

It depends on the type of video. On this occasion we will describe the most commonly used.

To stream high quality video over the Internet, H.264 is arguably the most widely used codec for most multimedia traffic. This codec is considered to be of excellent quality, coding speed and compression efficiency, although it is not as efficient as the later HEVC (High Efficiency Video Coding) compression standard, also known as H.265. H.264 also supports 4K video streaming, a real advance for a codec created in 2003.

Now that we have an overview of codecs, let’s look at some compression techniques.

Compression techniques

The most common compression technique is scaling the resolution. The higher the resolution of a video, the more information is contained in each picture. One way to reduce the amount of data is to reduce the size of the image and then scan it again. As a result, fewer pixels are generated, which reduces the level of detail of the image, which has a positive effect on the amount of information required. This process allows you to set multiple quality levels for a video that correspond to different resolutions created. A practical example is if you are watching a movie in streaming before playing it, you can actually choose the resolution at which you want to watch it, provided your device
Support him

One video compression technique that may not be widely used is the interframe. This process reduces “redundant” information from one frame to another.

Another technique is the P-frame, short for predictive frame, which means that it can look back at an i-frame or another P-frame and understand whether the same images are present. In this case, this part is excluded for reasons of space.

B-Frame, on the other hand, is the bidirectional predictive frame that offers good compression without affecting the viewing experience. However, this technique requires a higher coding profile.

Another technique is that which makes it possible to intervene in the color. This process, called “chroma subsampling”, tries to maintain the brightness of the image, which affects the quality of the color. Finally, another method of compressing videos is to reduce the number of frames per second.

Mp3: Audio Compression.

Audio Digitization.

Sound is a continuous wave that propagates through air or other media, formed by
pressure differences, so that it can be detected by measuring the pressure level in a
point. Sound waves have the proper and measurable characteristics of waves in general,
such as reflection, refraction and diffraction. As it is a continuous wave, a
digitization process to represent it as a series of numbers. Currently, most of
the operations carried out on sound signals are digital, since both storage and
processing and transmission of the signal in digital form offers very significant advantages over
analog methods. Digital technology is more advanced and offers greater possibilities, less
sensitivity to transmission noise and ability to include error protection codes,
as well as encryption. With the appropriate decoding mechanisms, moreover, they can be treated
simultaneously signals of different types transmitted on the same channel. The disadvantage
main aspect of the digital signal is that it requires a much greater bandwidth than that of the signal
analog, hence an exhaustive study is carried out regarding data compression,
some of whose techniques will be the center of our study.
The digitization process consists of two phases: sampling and quantization. In the sampling,
Divide the time axis into discrete segments: the sampling frequency will be the inverse of time
that mediates between one measurement and the next. At this time the quantization is performed, which, in its
In the simplest way, it is simply to measure the signal value in amplitude and save it.

Nyquist’s theorem guarantees that the frequency necessary to sample a signal that has its
Higher components at a given frequency f is at least 2f. Therefore, the range being
higher than human hearing around 20 Khz., the frequency that guarantees a sampling
suitable for any audible sound will be about 40 Khz. Specifically, to get sound
High-quality frequencies of 44.1 Khz are used, in the case of CD, for example, and up to 48 Khz.
in the case of the DAT. Other typical values are submultiples of the first, 22 and 11 Khz. According to
nature of the application of course the appropriate frequencies can be much lower
such that the voice process is usually carried out at a frequency of between 6 and 20 Khz. or
even less. Regarding quantization, it is evident that the more bits used for the
axis division of amplitude, the “finer” the partition will be and therefore the less error in attributing
a concrete amplitude to the sound at every moment. For example, 8 bits offer 256 levels of
quantization and 16, 65536. The dynamic range of human hearing is about 100 dB. The
axis division can be performed at equal intervals or according to a certain density function,
looking for more resolution in certain sections if the signal in question has more components in a certain
intensity zone, as we will see in the coding techniques.
The complete process is usually called PCM (Pulse Code Modulation) and so we
We will refer to it hereinafter. It has been described in a very simplistic way, mainly
because it is widely discussed and is well known, being the field of study of
this work. However, we will go into detail at any time that is necessary for the
development of the exhibition.
1.2 Coding and Compression.
Before describing compression and encoding systems, we must pause briefly.
analysis of human auditory perception, to understand why a quantity
Significant information that the PCM provides can be discarded. The heart of the matter,
as far as we are concerned, it is based on a phenomenon known as masking.
The human ear perceives a frequency range between 20 Hz. And 20 Khz. First of all, the
sensitivity is higher in the area around 2-4 Khz., so that the sound is more
hardly audible the closer to the ends of the scale. Second is the
masking, whose properties exhaustively use the most interesting algorithms:
when the component at a certain frequency of a signal has high energy, the ear cannot
perceive lower energy components at close frequencies, both lower and higher. TO
a certain distance from the masking frequency, the effect is reduced so much that
negligible; the range of frequencies in which the phenomenon occurs is called the critical band
(critical band). Components belonging to the same critical band influence each other and
they do not affect nor are affected by those that appear outside it

Audio Data compression

Data compression or the technique that changed everything

Without pretending to extend ourselves in the description of this critical concept, it is important to know that compression is understood as a scheme that allows, by means of a “decision” algorithm based on a series of “rules” (which in the case of audio are masking and audibility threshold) reduce the amount of data to transmit a certain message. In other words: if the song “x” occupies, in the format used to encode the sound of a CD, 1 million bits, the data compression allows that song to be reproduced with maximum intelligibility using only 50,000 of those bits.

In this way, the download of a complete CD from a certain website could be carried out in a reasonable period of time. But, of course, the price to pay was high in terms of quality because such “castration” of the original message (which in turn was not “continuous”, analog, but also digital, although “linear”, without compression) meant removing many nuances of music, a disaster that in reality did not care for many consumers but it did worry, and a lot, those who bet on that High Fidelity in the reproduction of the sound that we are so passionate about and who received a wound that was almost fatal . In this sense, it is worth knowing that the “philosophical” keys to data compression are summarized in two terms: redundancy and irrelevance. In the first case, it is about reordering the available data to eliminate the ones that are repeated (for whatever reason: security, etc.), a bit like a “zip” computer file. It is a formal remodeling that does not affect the sound message at all (but it does save space to transmit / save data, making it very practical), so in this case, we are talking about lossless compression or “lossless” ” It is the second term that has the greatest scope in terms of sound quality because the idea of irrelevance implies deleting irrelevant data from a certain message. And, of course, who decides what is relevant or not? Well, an algorithm, a program that, obviously, can be more or less sophisticated but still makes decisions with which everyone will agree. It is easy to understand: what may be irrelevant to such a person and / or the team may not be so to someone else. The fact is that here musical information is deleted, which, fundamentally, can no longer be recovered. Well, the algorithms in which there are losses of musical information are known as “lossy” or lossless coding algorithms. From what has been said, it is easily deduced that the difference between the concepts “lossless” and “lossy” is the one that marks the border between high and low quality digital audio, between high resolution (with recording studio quality formats or “Studio Master” on the cusp) and that “practical” sound (in principle for portable players and cars) and very often unnatural formats like the once ubiquitous MP3, which, we insist, almost ruined with the improvements provided by the CD.
ADSL, the key to accessing High End audio via the Internet
Basically it was a purely technical progress that, logically, had to come. A progress that allowed breaking the limitations that prevented downloading a song recorded in PCM at 16 bits / 44’1 kHz and, over time, the files with much higher resolution than for a good decade and a half are the usual ones in studios of recording. So, thanks to ADSL, the High End in audio via the Internet, and therefore “without physical support” is available to everyone. At this point, it will be good to briefly review the small “soup” of acronyms with which we can find ourselves, otherwise the result of the availability of open and “closed” environments (Windows, Mac), in what CODEC’s (algorithms that compress and decompress data (in this case of music) refers to the fact that compression is the norm.

AAC (Advanced Audio Coding): It was designed to be the successor to MP3 and, although it is a lossy CODEC, the results in terms of sound quality are superior to those of MP3 for the same bit rate. The AAC has adopted a wide range of portable audio devices such as the iPod and its derivatives for use.
AIFF (Audio Interchange File Format): It is the version of WAV created by Apple. Works with uncompressed (ie “lossless”) files that maintain full resolution and size.

ALE (Apple Lossless Encoder), also known as ALAC (Apple Lossless Audio Codec): Uses lossless compression to save storage space. Once unzipped for listening, the file will be bit by bit identical to a full size WAV or AIFF encoded file. As in AIFF or FLAC, in ALE / A files

Audio compression, an explanation

Audio compression can be somewhat confusing at first due to the fact that the tools to implement it often have many elements that interact with each other and can be a headache.

Added to all this is the fact that audio / sound compression is often confused with compression in terms of digital formats (MP3 for example), which is a much more complex principle.

That is why we made this guide that aims to attack the most common doubts regarding compressors. The ones I had and the ones you probably have at the moment.

Let’s move on to the important:

What are compressors?

They are essentially an automatic volume or level control.

Let me explain: They are the equivalent of the fader of a console operated by a person in real time, that person has the function of lowering the fader when the volume of an element suddenly rises excessively. All this to control the dynamic range of said element and prevent it from going out of plane.

So what the compressor does in essence is reduce the level of a signal with parameters that are set by the user and that modify how it behaves.

How do they work?

Threshold and knee audio compression
An example of an acting audio compressor showing a 4: 1 reduction contrasting it with the signal without any reduction (1: 1)

Comparing signals, that is to say: a signal enters the compressor, for example the voice we were talking about before and we set a certain level (threshold or treshold) which, if exceeded, causes the compressor to act reducing the level of said voice at the output as if it were the fader on a console.

So the compressor is all the time comparing the input signal against this threshold and reducing the signal at the output if it passes it. On the other hand, the amount of reduction at the output is not always the same, but can be modified by the user with another parameter.

What are all those knobs?

Compressors have various user-modifiable parameters that appear in the form of knobs on both digital and hardware models. Let’s see what they are:

Threshold or Treshold: we tell the compressor that if the signal goes above a certain level, it reduces it in gain. The lower the amount of signal enters the compression and therefore there will be greater reduction in gain. A detail to keep in mind is that in digital models the threshold will appear as a negative number, in essence the more negative that number is, the lower the threshold and the more signal is compressed.
Compression ratio or Ratio: here we tell the compressor to reduce the signal that exceeds the threshold by a certain proportion established by us. For example, if our signal passes the threshold by 10 decibels and we want it to decrease by 5 decibels, we put a ratio of 2: 1 (it works as a division). At higher rates, there will be a greater reduction, but also the compression may start to be noticeable, which that we generally don’t want to happen. What is sought is that it be transparent so that the listener does not realize that the signal was manipulated.

Attack or Attack: it is the time in seconds (generally in the order of milli seconds) that the compressor takes from the moment the signal passes the threshold to the complete reduction in gain that we set with the compression ratio. Keep in mind that the compressor essentially acts immediately, but it is this time that determines how it interacts with the envelope of the signal to be compressed.

Release: is the time in milli seconds that the compressor takes to return to unity gain once the signal stops being above the set threshold. In the same way that with the attack the release can modify the envelope of the sound in question and therefore is very important in the operation of the compressor.

Knee: it is a parameter found in some compressors that modifies the way in which the compressor begins to act, the name is due to the fact that the curve that describes the way in which the compressor begins to act is similar to a knee (knee in English ).
So that we understand better when we talk about soft knee we are talking about that the compressor starts to act gradually before the set threshold and reaches its compression ratio established in this way. Instead, a hard knee compressor will only act when the signal goes beyond the established threshold and therefore more aggressively.

Make up gain or output gain: is the parameter that controls the compressor’s output gain, after having activated and reduced the signal by a number of decibels. What is sought in general is that what was reduced in level is re-gained and therefore make the parts that had less volume now approach those that were compressed.

What is audio compression?

I have finally returned to the tutorials, we are going to talk about the compression of audio from the most basic to the most advanced, it is a subject that many as producers have had a hard time learning and understanding.

So what is audio compression and what can you do to help?

Basically, compression reduces the dynamic range of your recording by reducing the level of the loudest parts, which means that the noisy and silent parts are now closer together in volume and the natural volume variations are less obvious. The audio compressor unit can increase the overall level of this compressed signal.

So, the end result is that the quieter parts sound as if they had increased their volume to be closer to the louder parts. Dynamic changes in the volume of a recording are now under more control, and a side effect is that the overall level of the compressed recording can be increased within its mix. The recording will also be located within the entire mix much more easily.

What are the compression controls?

The compression device itself has many different controls that can affect the sound it is processing. We will review the main controls that are commonly found.

Input Gain
This controls the level of the signal entering the audio compressor.
Threshold
Compression reduces the overall level of the loudest parts of your recording. But how does the compressor know what part of the signal is “high” and what part of the signal is compressed? When setting the threshold.
The threshold sets the level at which the compressor starts and begins to change the recording dynamics. So, for example, if you set your threshold to -20 dB, everything below this level will not be affected by the compressor. But everything higher than this level (-20 dB) will be compressed.
Ratio
How much will the signal be compressed once it has exceeded this threshold? This is controlled with the relationship. The higher the ratio, the greater the compression.
The easiest way to show you how reason works is by showing you some numbers, if the ratio is 1: 1, there is no compression at all. On the other hand, if the ratio is set to 2: 1, for every 2 dB of sound that exceeds the threshold, you will get 1 dB of output above the threshold. So, if the signal exceeds the threshold by 10 dB, the compressor reduces this signal, so it is now 5 dB above the threshold.
If the ratio goes up to 8: 1, for every 8 dB of sound above the threshold you would get 1 dB of output above the threshold. Then, if the signal exceeds the threshold by 16 dB, the compressor reduces it, so only 2 dB exceeds the threshold.
Attack
This is the time it takes for the compressor to act on the input, once the sound level has exceeded the threshold. It is usually measured in milliseconds (ms).
Release
This is the time it takes for the compressor to let the signal return to normal once it has fallen below the threshold. Again, usually measured in ms.
Makeup
If the audio signal has been compressed, the overall level of the signal will be reduced. Increasing the output gain increases the level that comes out of the compressor, so the volume can more easily adapt to the levels of the rest of its tracks in its mix.
Knee
The soft compression of the knee is softer in the sound as it passes through the audio compressor: the change of uncompressed sound to compressed is softer. Hard knee compression is a more immediate and obvious effect.
Compressors are a very effective tool for us engineers, in the next post I will talk about the different types of compressors.