A Whirlwind Tour about the H.264 Advanced Video Coding |

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15.04.2019 07:16:11 - H.264 is getting so much attention because it can encode video with approximately 3 times
fewer bits than comparable MPEG-2 encoders.

( - Why the buzz about H.264? It's the bitrate!


H.264 is getting so much attention because it can encode video with approximately 3 times

fewer bits than comparable MPEG-2 encoders. This opens new possibilities such as:

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Squeezing more television programs into a given channel bandwidth;

Delivering quality video over bandwidth-constrained networks (e.g., 3 and 4G Mobile),

Fitting a high-definition movie feature onto


a standard DVD.

Because H.264 is up to twice as efficient as MPEG-4 Part 2 (natural video) encoding, it has recently been welcomed into the MPEG-4 standard as Part 10 – Advanced Video Coding. Many established encoder and decoder vendors are moving directly to H.264 and skipping the intermediate step of MPEG-4 Part 2.

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If you have some experience with video compression, the best way to appreciate the buzz is to run a run a case yourself. An easy approach is to acquire our Expert-H264 demo and interactively encode video content from a variety of popular formats.

In either case, the resulting .26L file will seem too small to be believed. When you run the decoder and view the decoded file, you will be amazed at how good the quality is at such a low bit rate.

Goals & Approach of H.264

The International Telecommunications Union (ITU) initiated the h.26L (for long term) effort in 1998 as a continuation of work following the MPEG-2 and H.263 standards. The overriding goal was to achieve a factor-of-2 reduction in bit rate compared to any competing standard.

Recall that MPEG-2 was optimized with specific focus on Standard and High Definition digital television services, which are delivered via circuit-switched head-end networks to dedicated satellite uplinks, cable infrastructure or terrestrial facilities. MPEG2's ability to cope is being strained as the range of delivery media expands to include heterogeneous mobile networks, packet-switched IP networks, and multiple storage formats, and as the variety of services grows to include multimedia messaging, increased use of HDTV, and others. Thus, a second goal for H.264 was to accommodate a wider variety of bandwidth requirements, picture formats, and unfriendly network environments that throw high jitter, packet loss, and bandwidth instability into the mix.

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The H.264 approach is a strictly evolutionary extension of the block-based encoding approach so well established in the MPEG and ITU standards. Key steps include:

Use of Motion Estimation to support Inter-picture prediction for eliminating temporal redundancies

Use of spatial correlation of data to provide Intra-picture prediction.

Construction of residuals as the difference between predicted images and source images.

Use of a discrete spatial transform and filtering to eliminate spatial redundancies in the residuals.

Entropy coding of the transformed residual coefficients and of the supporting data such as motion vectors.

Although H.264 introduces carries several techniques that push the block based approach up to the limits of its efficiency. It is not a fundamentally different approach, but rather a significant refinement of well-established methods.

Major Features of H.264

To understand the new features of H.264, it is assumed that you are familiar with the approach and terminology used in MPEG 1 & 2 – if not, there are many fine books and reviews on this subject. For example, you can go to a useful MPEG-2 tutorial for a summary of MPEG-2 video and systems.

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Now we will summarize the key features and point you to some useful background material. Note that some H.264 features not supported by initial profiles are identified by an asterisk (*).

Improved Inter-Prediction and Motion Estimation

First recall the limitations of motion estimation in MPEG-2, which searches reference pictures for a 16x16 set of pixels that closely matches the current macro block. The matching set of pixels must be completely within the reference picture. In contrast, H.264 provides:

Fine-grained motion estimation. Temporal search seeks matching sub-macro blocks of variable size as small as 4x4, and finds the motion vector to _ pel resolution. Searches may also identify motion vectors associated with matching sub-macro blocks of 4x8, 8x4, 8x8, 8x16, 16x8, or the full 16x16. In future, even finer 1/8 pel resolution will be supported.

Multiple reference frames. H.264 provides additional flexibility for frames to point to more than multiple frames – which may be any combination of past and future frames. This capability provides opportunities for more precise inter-prediction, but also improved robustness to lost picture data.

Unrestricted motion search. Motion search allows for reference frames that may be partly outside the picture; missing data can be spatially predicted from boundary data. Users may choose to disable this feature by specifying a Restricted Motion search.

Motion vector prediction. Where sufficient temporal correlation exists, motion vectors may be accurately predicted and only their residuals transmitted explicitly in the bit stream.

Such techniques not only provide for more accurate inter-prediction, but also help to partition and scale the bitstream with priority given to data that is more globally applicable. Thus, they not only improve compression but also resilience to errors and network instabilities.

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