MP4 Compression Techniques

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MP4 Compression Techniques

Let’s talk about MP4 compression techniques

As a video encoding specialist, I’m constantly exploring ways to optimize video files for size and quality. Understanding MP4 compression techniques is essential for anyone involved in video production, streaming, or distribution. Properly compressing MP4 files ensures they are manageable, stream efficiently, and maintain good visual fidelity.

What is MP4 Compression and Why Is It Necessary?

MP4 compression involves reducing the file size of a video while preserving acceptable quality. I often encounter situations where uncompressed video files are enormous, making them impractical for storage and distribution. Imagine trying to share a 4K video recording from your phone – the file size could be several gigabytes! MP4 compression techniques address this issue by using algorithms to remove redundant or less important data, resulting in smaller, more manageable files.

Lossy vs. Lossless MP4 Compression: Understanding the Trade-Offs

MP4 compression can be achieved through lossy or lossless methods. I always consider the trade-offs between file size and quality when choosing a compression technique.

* Lossy Compression: Removes some of the original data to achieve smaller file sizes. This can result in a slight reduction in quality, but it’s often imperceptible to the human eye. Common lossy codecs include H.264 and H.265.
* Lossless Compression: Preserves all of the original data, resulting in no loss of quality. However, lossless compression typically results in larger file sizes compared to lossy compression.

Key Codecs Used in MP4 Compression: H.264, H.265, and AV1

The choice of codec significantly impacts the effectiveness of MP4 compression. I’ve worked extensively with H.264, H.265, and AV1, and each has its strengths and weaknesses.

* H.264 (AVC): A widely supported codec that provides a good balance of quality and compression. It’s compatible with most devices and platforms.
* H.265 (HEVC): Offers better compression efficiency than H.264, resulting in smaller file sizes with comparable quality. However, it requires more processing power and may not be supported by older devices.
* AV1: A newer, open-source codec that aims to provide even better compression efficiency than H.265. It’s gaining popularity but may not be as widely supported as H.264 or H.265.

Bit Rate: Controlling MP4 File Size and Quality

Bit rate measures the amount of data used to encode a video per unit of time, typically expressed in megabits per second (Mbps). I always carefully adjust the bit rate to achieve the desired balance of file size and quality. A higher bit rate generally results in better video quality but also increases the file size. Conversely, a lower bit rate results in smaller file sizes but may reduce video quality.

Frame Rate: Balancing Smoothness and File Size

Frame rate refers to the number of frames displayed per second (fps), affecting the smoothness of motion in a video. I often adjust the frame rate to optimize for different viewing scenarios. Common frame rates include 24fps (cinematic look), 30fps (standard for television), and 60fps (smoother motion). Reducing the frame rate can decrease file size but may also make the video appear choppy.

Resolution: Optimizing for Different Screens

Resolution refers to the number of pixels in a video frame, determining the level of detail. I always consider the target viewing device when setting the resolution. Higher resolutions, like 4K (3840 x 2160) or 1080p (1920 x 1080), provide sharper and more detailed images compared to lower resolutions like 720p (1280 x 720) or 480p (854 x 480). Reducing the resolution can significantly decrease file size, but it may also make the video appear blurry on larger screens.

Chroma Subsampling: Reducing Color Data

Chroma subsampling is a technique used to reduce the amount of color data in a video. I often use chroma subsampling to further compress MP4 files without significantly impacting perceived quality. The human eye is more sensitive to changes in brightness (luma) than changes in color (chroma), so reducing the chroma data can result in smaller file sizes with minimal visual impact. Common chroma subsampling formats include 4:2:0, 4:2:2, and 4:4:4.

Variable Bit Rate (VBR) vs. Constant Bit Rate (CBR) Encoding

Choosing between variable bit rate (VBR) and constant bit rate (CBR) encoding can impact both file size and quality. I generally prefer VBR encoding for its ability to adapt to the complexity of the video content.

* Variable Bit Rate (VBR): Dynamically adjusts the bit rate based on the complexity of the scene. This results in better quality for complex scenes and smaller file sizes for simpler scenes.
* Constant Bit Rate (CBR): Uses a fixed bit rate throughout the entire video. This is simpler to implement but may result in wasted bandwidth for simpler scenes and reduced quality for complex scenes.

Two-Pass Encoding: Maximizing MP4 Compression Efficiency

Two-pass encoding is a technique that can improve MP4 compression efficiency. I often use two-pass encoding for critical projects where quality is paramount. In the first pass, the encoder analyzes the entire video to determine the optimal bit rate allocation. In the second pass, the encoder uses this information to create the final compressed video. This can result in better quality compared to single-pass encoding.

Optimizing MP4 Compression for Streaming Platforms

Streaming platforms like YouTube, Netflix, and Vimeo have specific recommendations for MP4 compression settings. I always consult these recommendations to ensure my videos are optimized for their respective platforms. These recommendations typically include guidelines for resolution, bit rate, frame rate, and codecs.

Common MP4 Compression Mistakes to Avoid

Even experienced video editors can make mistakes during MP4 compression. I’ve learned to avoid common pitfalls by being meticulous and paying close attention to detail. These include using too low a bit rate, choosing the wrong codec, ignoring the target platform, and neglecting audio settings.

Latest words on MP4 compression techniques

In conclusion, mastering MP4 compression techniques is essential for creating video files that are both high-quality and manageable in size. By understanding the various factors involved, such as codecs, bit rate, frame rate, and resolution, you can optimize your videos for different viewing scenarios. Remember to always experiment and test different settings to achieve the desired balance of quality and file size. Also, remember that Mp4Gain is the appropiate solution to achieve professional-sounding audio.

FAQ about MP4 compression techniques

What is MP4 compression and why is it important?

MP4 compression lessens video sizes while retaining quality so things store and ship smoothly. Large file sizes do not work well at all, without it.

Can lossy and lossless techniques both be used during the compressions?

Yes, and each has its own give-and-take. Lossy squeezes and can hit the looks lightly but, makes it small. Lossless holds every detail without the squeeze, so expect larger files.

What are codecs and how do they work in the world of media?

Codecs are what shrink and grow data for media to be played smoothly on devices. Common codecs used in MP4 compression techniques, are H.264, H.265, AV1.

Talk about the bit rate and what that’s involved with?

Bit rate labels bits moved for the video. More bits make better video, fewer make worse, as the numbers show in megabits per second (Mbps).

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What is the meaning for the term “frame rate” and how may it have an effect to the way a MP4 looks?

Frame rate labels frames each second. More frames means motion is easy, and fewer makes the video look jittery. Think 24fps versus a smoother 60fps.

What are some settings to consider for video in screens?

Consider the devices that play a video to set for those devices and remember, more pixels creates a much better image. So keep that in focus with your compression workflow.

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Clarify the term “chroma subsampling“?

Chroma subsampling trims all colors because human eyes give emphasis to brightness, leading to greater compression with nominal visual change. The main values are 4:4:4, 4:2:2, and 4:2:0.

What’s best choice for VBR versus CBR?

VBR, is the better process that tunes the sound according to the action in that frame. It is a bit dynamic versus CBR which is static.

How does two-pass come into the picture, and what is it?

Two passes gives compression a lift. The first finds all aspects, second tunes everything to make the audio as solid as it can be given what one has on hand.

When you think of the best methods to tweak, what actions must be taken?

It is best to check the compression parameters to see if the right choices where made or not for the media. That creates an audio that works within parameters.

Comments:

Cheers. That really spells things out, now getting video size and quality clicks and makes sense, thanks again!

Oh, okay – you got it to explain the numbers in a clean way for my band. This is what we need to know. So solid and we are moving forward with tips in mind.

Respect and good luck to you – for laying out what to think over when fixing up media and videos.

Is pretty much knowing that you can trade the size and the looks, depending on gear that will play it – am learning and appreciate this breakdown

Any killer app name drop, please? What can a greenie like me use?

Bless you, great creator! The content just hit all points and really made for a solid quick lesson.

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Impact of Quantization Matrices on MP4 Quality

Let’s talk about the impact of quantization matrices on MP4 quality

When it comes to MP4 quality, quantization matrices play a pivotal role in determining how much detail is retained or lost during compression. As someone deeply involved in video encoding and optimization, I’ve seen how these matrices can make or break the visual appeal of a video. They essentially dictate how compression algorithms prioritize certain frequencies over others, affecting the clarity, sharpness, and overall fidelity of the video.

Imagine this: You’re editing a photo and need to reduce its file size. If you reduce every part of the image equally, the overall quality diminishes evenly. However, if you could selectively reduce detail in the background while keeping the main subject sharp, the result would look much better. That’s what quantization matrices do for video. They allow certain details to remain intact while compressing less noticeable parts. This nuanced control has a direct impact on MP4 quality, making it an indispensable aspect of video compression.

Understanding what quantization matrices are

Quantization matrices are essentially blueprints that guide compression algorithms in deciding which parts of the video data to keep and which to discard. They work by assigning weights to different frequency components in the video, influencing how much compression is applied to each.

In simpler terms, think of a quantization matrix as a map that shows where to save space and where to preserve details. For instance, if a scene in a video has a bright sky and detailed buildings, the matrix might allow for more compression in the sky (which is uniform) and less in the buildings (which are intricate). This balancing act is crucial for achieving efficient compression without compromising perceived quality.

Why quantization matrices matter for MP4 quality

The choice of quantization matrices significantly affects MP4 quality because they control how visible artifacts—like blockiness or blurring—appear after compression. When the wrong matrix is used, you might end up with a file that’s small but riddled with visual flaws. On the other hand, a well-optimized matrix ensures the video looks crisp and professional, even at reduced file sizes.

I’ve worked with projects where fine-tuning the quantization matrices led to significant improvements in quality without ballooning the file size. For instance, a sports video with fast-moving players and a static audience can benefit from a custom matrix that allocates more detail to motion-heavy areas. The result? A sharper, more engaging viewing experience.

How quantization matrices work in video encoding

Quantization matrices operate by breaking video data into smaller chunks and analyzing their frequency components. Higher frequencies correspond to fine details, while lower frequencies relate to broader, uniform areas. The matrix assigns a priority to each frequency, determining how much of it to preserve.

For example, during the encoding of an MP4, the algorithm uses the quantization matrix to decide how much detail to keep in textures, edges, and transitions. By compressing low-priority areas more aggressively, it reduces file size while keeping the viewer’s focus on the critical parts of the scene. This approach mimics how the human eye perceives detail, prioritizing the elements that are most noticeable.

Real-world examples of quantization matrix optimization

In one project, I helped optimize training videos for a corporate client. These videos needed to look great on large screens but still fit within strict storage limits. By customizing the quantization matrices, I was able to maintain sharp text and clear diagrams while compressing the less critical background elements. This approach saved gigabytes of space without sacrificing quality.

Another instance involved a nature documentary where the focus was on preserving intricate details in animal fur and leaves. A generic matrix would have smoothed out these details, but by tailoring the matrix to prioritize high frequencies in these areas, we achieved stunning visual results. The final MP4 files were not only compact but also visually immersive.

The balance between compression and quality

Striking the right balance between compression and quality is an art, and quantization matrices are the brush. Using overly aggressive matrices might save space, but it can lead to artifacts that ruin the viewing experience. On the flip side, overly lenient matrices preserve every detail but result in massive file sizes.

I always recommend experimenting with different matrices to find the sweet spot. For instance, action movies and gaming videos require matrices that prioritize motion clarity, while documentaries might focus on preserving texture and color depth. Each type of content benefits from a tailored approach, ensuring the MP4 delivers an excellent viewing experience.

Advanced techniques for customizing quantization matrices

For those deeply invested in video quality, customizing quantization matrices offers unparalleled control. Most encoding software allows you to tweak these matrices or even upload custom ones. By analyzing the content of your video, you can adjust the matrix to prioritize the most visually important elements.

For example, when encoding a video for e-learning, I prioritize text and diagrams, ensuring they remain sharp even after compression. Similarly, for music videos, I focus on preserving color gradients and dynamic lighting, which are crucial for aesthetic appeal. These adjustments often involve trial and error, but the payoff is worth the effort.

MP4 encoding standards and quantization matrices

MP4 encoding standards like H.264 and H.265 incorporate predefined quantization matrices, but these can be adjusted for specific needs. The default settings are designed to provide a good balance, but they might not suit all scenarios.

In my experience, using custom matrices tailored to the content type can yield significantly better results. For instance, H.265’s flexibility allows for more granular adjustments, making it ideal for high-definition content. By experimenting with these settings, you can achieve compression ratios that were previously unattainable.

Latest words on the impact of quantization matrices on MP4 quality

Quantization matrices are a critical component of MP4 compression, directly influencing the balance between quality and file size. By understanding how they work and applying them strategically, you can achieve remarkable results. Whether you’re encoding videos for streaming, storage, or playback, fine-tuning these matrices can make a noticeable difference.

If you’re looking for a tool to manage your video quality with precision, Mp4Gain offers advanced options to normalize and optimize your MP4 files. It’s an excellent solution for ensuring your videos look their best while staying within size constraints.

FAQs about the impact of quantization matrices on MP4 quality

What are quantization matrices in MP4 encoding?

Quantization matrices are tools used in video encoding to prioritize certain details during compression. They assign weights to different frequency components, determining what to preserve and what to compress more aggressively.

How do quantization matrices affect video quality?

They influence the balance between detail retention and file size. Properly optimized matrices minimize visible artifacts while maintaining clarity in important areas.

Can I customize quantization matrices?

Yes, many encoding tools allow customization of quantization matrices to suit specific video content, offering greater control over quality and compression.

Are there default quantization matrices in MP4 standards?

Yes, encoding standards like H.264 and H.265 include default matrices designed to provide a balance between quality and compression. However, these can be adjusted.

What content benefits most from custom quantization matrices?

Content with specific visual priorities, like action scenes or text-heavy educational videos, benefits from custom matrices tailored to preserve essential details.

Do quantization matrices impact file size?

Yes, by selectively compressing less noticeable details, quantization matrices can reduce file size while maintaining perceived quality.

What role do quantization matrices play in H.265 encoding?

In H.265, matrices allow for more precise adjustments, making it ideal for high-definition content and achieving better compression ratios.

Are quantization matrices necessary for all MP4 files?

While not mandatory, they are essential for optimizing quality and file size, especially in professional applications or high-compression scenarios.

Can poor quantization matrices ruin MP4 quality?

Yes, poorly designed matrices can introduce visible artifacts like blockiness and blurring, degrading the viewing experience.

What tools are best for managing quantization matrices?

Professional encoding software often provides options for customizing quantization matrices. Tools like Mp4Gain help normalize and optimize MP4 files efficiently.

Comments:

Wow, I didn’t know quantization matrices could make such a difference! I’ve always wondered why some videos look great even when compressed. Great info here.

Really helpful article, but I wish there were more examples of specific software settings for beginners like me. Maybe a guide could help?

I’ve been trying to compress gaming videos, and this makes sense now! Custom matrices are definitely the way to go for motion-heavy content.

This is one of the best explanations I’ve found online. It’s clear and detailed without being overly technical. Thanks for sharing!

Can you add more about how matrices affect audio tracks in MP4 files? I feel like there’s a gap there.

The nature documentary example was spot on. I’ve had issues with textures being lost in wildlife videos. Great tip on custom matrices!

Didn’t know H.265 allowed for such precise adjustments. Makes me want to revisit some older projects to see what I can improve.

Bitrate control methods in MP4 encoding

Let’s talk about Bitrate control methods in MP4 encoding

Bitrate control in MP4 encoding is a crucial aspect when you want to strike the perfect balance between file size and video quality. Having worked with MP4 encoding for years, I can confidently say that mastering bitrate control will make a world of difference. It’s like adjusting the quality of your video, similar to how a photographer sets the right aperture for a perfect shot. If you set the bitrate too low, you risk poor quality, but if it’s too high, you end up with unnecessarily large files. Here, I’ll break down the various bitrate control methods that can help you get the best results.

What is bitrate control and why does it matter?

Bitrate control is all about managing how much data is allocated to encode a video in MP4 format. The bitrate directly affects the final output in terms of video quality and file size. A higher bitrate means better quality but larger files, while a lower bitrate reduces file size at the cost of video clarity.

When I first started working with MP4 encoding, I didn’t realize how critical bitrate was. After a few projects, I quickly learned that controlling the bitrate correctly could turn a decent video into an exceptional one. It’s like when you’re watching a stream; if the bitrate is too low, the video stutters or becomes blurry. If it’s too high, the stream takes forever to load.

Types of bitrate control methods in MP4 encoding

There are several methods of bitrate control in MP4 encoding, each suited for different types of projects. Here are the most common methods I’ve used and what I recommend.

Constant Bitrate (CBR)

CBR is one of the oldest and most basic bitrate control methods. It involves setting a fixed bitrate throughout the entire encoding process. The main advantage of CBR is its predictability. You know exactly what size your file will be, which can be useful when you’re working within strict size limitations.

However, CBR has its downsides. If the video has fast motion or complex scenes, the quality can degrade, as the bitrate remains the same despite the varying demands of different scenes. It’s like trying to pour the same amount of water into different-sized containers; it works, but it’s not always the most efficient.

Variable Bitrate (VBR)

VBR, on the other hand, is a more advanced approach that adjusts the bitrate depending on the complexity of the video content. The bitrate is higher during complex scenes and lower during simpler parts. This method delivers better quality at smaller file sizes, which is why I often recommend it for most modern video encoding projects.

One thing to keep in mind with VBR is that it can take longer to encode since the bitrate is constantly changing. But if you’re working on a high-quality video project and you want the best results, VBR is usually the way to go.

Average Bitrate (ABR)

ABR is a hybrid of CBR and VBR. It averages the bitrate across the entire video but allows for some fluctuation based on scene complexity. It’s less predictable than CBR but more efficient than VBR in terms of speed. This makes it an excellent choice for those who want good video quality without the need for long encoding times.

If you’re encoding videos for streaming platforms, ABR could be your best friend, as it strikes a balance between quality and file size. It’s like having a smart playlist that adjusts the volume just right so that each song plays at the perfect level.

Real-life examples of bitrate control

I’ve worked on many projects where selecting the right bitrate control method was critical. For instance, when I encoded a documentary for a client, I used VBR because the video included both fast-moving action scenes and long static shots. The VBR method ensured that I didn’t lose any quality in the fast-paced scenes while keeping the file size manageable.

In another project, a client needed a video for a mobile app, and they had strict file size limits. For this, I opted for CBR because I knew exactly how big the file would be, and it helped avoid unpredictable buffering or loading issues on users’ devices.

Choosing the right bitrate control method

Choosing the right bitrate control method depends largely on the specific requirements of your video project. If you’re targeting a high-quality final product and have the time to dedicate to encoding, VBR is often the best choice. On the other hand, if you need fast encoding times and predictable file sizes, CBR might be more appropriate.

Here are some factors to consider when making your choice:

Video content complexity: If your video has lots of fast action scenes, VBR may be a better fit.
File size constraints: CBR can be helpful if you need to stay within a certain file size, like for streaming.
Encoding time: If you’re on a tight schedule, ABR or CBR might save you time.
Quality preference: If the video quality is your top priority, VBR should be your go-to method.

Latest words on Bitrate control methods in MP4 encoding

As a specialist in MP4 encoding, I can say that mastering bitrate control methods is essential for any project. Whether you’re encoding videos for streaming, web use, or personal archives, the method you choose can significantly impact both the quality and efficiency of your workflow. By understanding the strengths and weaknesses of each bitrate control method, you can make informed decisions that result in better videos and more efficient encoding processes.

If you find that your video projects are not performing the way you’d like in terms of quality and file size, experimenting with these bitrate control methods is a good place to start. And remember, Mp4Gain is the perfect solution if you’re looking for a tool to help you achieve the ideal balance between file size and video quality.

Frequently Asked Questions (FAQ) on Bitrate Control Methods in MP4 Encoding

What is bitrate control in MP4 encoding?

Bitrate control refers to the method used to allocate data during the encoding of an MP4 video file. It impacts both the quality and the size of the final video. By controlling the bitrate, you can either prioritize file size or video quality depending on the method used. Common methods include Constant Bitrate (CBR), Variable Bitrate (VBR), and Average Bitrate (ABR).

What is the difference between Constant Bitrate (CBR) and Variable Bitrate (VBR)?

CBR maintains a fixed bitrate throughout the entire video, ensuring consistent file size but potentially sacrificing quality during complex scenes. VBR, on the other hand, adjusts the bitrate based on the complexity of the video content, offering better video quality at a smaller file size, especially for videos with diverse scenes.

Which bitrate control method should I use for my video project?

The best method depends on your project’s requirements. If file size is critical and you need predictability, CBR is a good choice. For high-quality videos where the content varies greatly, VBR provides better results. ABR is a good middle ground, offering a balance between quality and encoding speed.

Is VBR always better than CBR?

Not always. VBR is better when video quality is the priority, especially for complex scenes. However, CBR is more efficient when file size must be tightly controlled or when encoding time is a critical factor. It depends on your specific needs and the type of video you’re working on.

What are the benefits of using Average Bitrate (ABR) for MP4 encoding?

ABR offers a balance between CBR and VBR by maintaining an average bitrate over the entire video. It provides reasonable video quality while keeping file sizes manageable, making it ideal for streaming or situations where a good balance between quality and size is needed.

How do I choose the right bitrate control method for streaming?

For streaming, I recommend using ABR or VBR, depending on your platform and audience. ABR ensures faster streaming with a consistent experience, while VBR offers better quality for high-resolution or action-packed content. Both methods adapt to network conditions, improving the user experience.

How does bitrate affect the video file size?

Higher bitrates result in larger video files because more data is used to encode each frame, which increases video quality. On the other hand, lower bitrates reduce the video quality but also shrink the file size. It’s a balance between maintaining quality and minimizing file size, which is why bitrate control is crucial.

Comments:

This article really cleared up some of the confusion I had with CBR and VBR. I was using CBR for everything, but now I see VBR might be better for my action-heavy content. Thanks for sharing these tips! – VideoGeek

I had no idea about the ABR method! I’m going to try it for my next project since it sounds like a good middle ground. Thanks for the info! – PixelMaster

This was super helpful! I was stuck deciding between VBR and CBR for an upcoming video. Your advice on using VBR for complex scenes really helped. – SteveO

Honestly, I didn’t think bitrate control mattered that much until I started doing videos for my business. After reading this, I can see how important it is. – OliviaW

The real-life examples are so helpful. I’ve always struggled with figuring out what bitrate to choose, but now I get it. – TechyTim

This article is great, but I was hoping for more details on how to calculate the bitrate for my specific project. Maybe you could dive deeper into that next time? – CuriousCoder

What’s the best bitrate control for mobile streaming? I usually go with CBR, but I feel like I’m missing out on something better. – StreamerSarah

Really enjoyed this! I’ve been using VBR for my videos, and now I feel even more confident about it. – RealFilmFan

Had no idea there were so many options for bitrate control. This article helped me a lot with my next video project. – VideoJunkie

Great read! I still feel a bit confused about ABR, but I’ll try it next time. – JoshH

The secrets of how MP4 film and video compression works

You watch videos on an electronic device, tablet, smartphone or PC every day, but have you ever wondered how they work?

If we can stream high-definition films on our computers today, it is ideal for the technologies that have been developed over the past 30 years and that have revolutionized our view of digital film archiving. Technologies that are part of video compression systems.

How does a video work?

In general, a video is nothing more than a series of photos that appear in quick succession as quickly as possible.

By displaying the images in succession on the order of a few tens per second, it is possible to achieve the motion effect typical of films.

In particular, the video we see every day generally shows 24 to 25 frames per second. The number of frames per second displayed in a video is called the frame rate or even FPS (frames per second), which you have probably heard in the field of video games.

Video compression

If you do a quick calculation, it is clear that displaying 25 frames per second and saving exactly as you would save a photo on your computer would reach dimensions that are not realistic in terms of space.

A short example: A medium resolution photo in JPEG requires 300 KB. If 25 photos per second have to be displayed, we need 7.5 MB per second. So a 1 hour movie would be 27 GB. Considering that a DVD can generally hold 4.7 GB of data, this would mean that the average movie should be spread over a dozen DVDs, with the effort required to replace the disc every ten minutes of the movie .

Fortunately, we have managed to find a smarter way to play these films, and today we are generally used to recording video in kbps. H. eighth KB per second.

An hour of 300 kbps video only consumes 135 MB, much less than the previous 27 GB, and a value that allows you to realistically transfer these videos over the Internet, creating systems like YouTube, Netflix, and the competition.

Reducing the size of these videos is called “compression”. We generally speak of lossy compression, which is a type of compression that results in a slight loss of quality, most of which is aimed at being invisible to the eye. Human.

The higher the compression, the greater the loss of quality, of course. And if poorly compressed video can be of very high quality if you increase the compression, you will easily get into the mistake of moving around the screen.

How does video compression work?

The compression process of a video is quite long and varied. A lot depends on the type of format used. MPEG2, H264, WEBM … There are dozens of ways to compress a video, and they all give more or less different results depending on the video type.

In principle, however, all of these video compression formats have some strengths in common, which we will describe below.

First we said that the video consists of a series of pictures and that we have to show all of these pictures one after the other to show the video.

The problem is that storing all of these images takes up a lot of space. To save space, video formats generally don’t save all of the images. However, you save a single frame for every N images. Usually a complete picture is saved every 12 pictures. Of the remaining 11, only the parts of the image that have changed from the previous image are saved.

This way, instead of having to save 12 whole images, we can save the first in its entirety and then only the piece that changes between the first and the second, then only the piece that changes between the second and the third and so on.

The images that are completely saved are called I-FRAME and those whose only difference from the previous image is P-FRAME.

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