Overview of Digital Video Compression

Multimedia Systems and StandardsS2 IF Telkom University

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Agenda1. Background2. Why video compression?3. User requirement from video4. Video coding schemes

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Background1. Raw video signals requires a high

capacity2. Low complexity video coding

algorithms must be defined to efficiently compress video sequences for storage and transmission purposes

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Why video compression?1. Transmission: any network

huge bandwidth requirements2. Raw video: 320x200 pixel; 8

bit/pixel; 25 frame/secBandwidth to transmit

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From a network perspective

coded video streams are to be transmitted over a variety of networking platforms.

in the form of packets whose structure and size depend on the underlying transport protocols

packets are exposed to channel errors and excessive delays information loss error handling mechanisms

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Video coding technologyGoals:

to optimize the compression efficiency; and to meet quality of service of standard video coders

Evolutionnovel signal compression techniques

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Video coding selectionNormally depends on the bandwidth availability and the minimum quality required

Exp:• Video surveillance• Video call• Entertainment video• Telemedicine

Quality application dependentBandwidth bit / frame rate

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Typical RequirementsVideo quality and bandwidthComplexitySynchronizationDelay

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Video Quality & Bandwidththe two most important factorsHigher bit rate = better qualityit is necessary to tradeoff the network capacity against the perceptual video quality in order to come up with the optimal performance of a video service and an optimal use of the underlying network resources

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Other factorsAlso influence the video quality and

the bit rate:frame rate number of intensity and color levels image size spatial resolution

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Quality?perceptual qualityDesign metric for multimedia communication networks and applications developmentVia Network: channel errors and information loss user requirement: video coding algorithms are robust to errors

to mitigate the disastrous effects of errors secure an acceptable quality of service at the receiving end

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The complexity of a video coding alg.

Big-O?Common indicator = FLOPsFor real-time communication applications, low cost real-time implementation of the video coder is desirableRelated = power consumption

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SynchronizationSynchronization between various traffic streams must be maintained in order to ensure satisfactory performanceThe simplest and most common technique: buffer the received data and release it as a common playback point

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Another approachto assign a global timing relationship to all traffic generators in order to preserve their temporal consistency at the receiving end. This necessitates the presence of some network jitter control mechanism

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DelayIn real-time applications, the time delay between encoding of a frame and its decoding at the receiver must be kept to a minimum. Delays:

codec processing data buffering Long queuing delays in the network.

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Time delay in video coding

content-based tends to change with the amount of activity in the scene, growing longer as movement increases.

Long coding delays lead to quality reduction in video communications

a compromise has to be made between picture quality, temporal resolution and coding delay.

Time delays greater than 0.5 second are usually annoying and cause synchronization problems with other session participants

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Recommendations for universal image and video coding algorithmssince 1985 by ISO and ITU1st image coding standard: JPEG

by ISO in 1989 later by ITU-T

1st draft of a video coding standard: MPEG-1

December 1991 by ISO for audiovisual storage on CD-ROM at 1.5—2 Mbit/s.

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Recommendation….ITU-T H.261:

1990, CCITT first video coding standard 1993, subsumed into an ITU-T published recommendation For low bit rate communications over ISDN networks at p64 kbit/s.

ITU-T H.262 (known as MPEG-2):1994 for HDTV applications at 4—9 Mbit/s.

ITU-T H.263: 1996for very low bit rate communications over PSTN networks at less than 64 kbit/s

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Further worksAnnexes: H.263+ (1998) and H.263++ (1999) MPEG-4:

1998, by ISO MPEG AVT (Audio Video Transport) group for mobile audiovisual communications. Using the object-based strategy in its layering structure (as opposed to the block-based frame structure in its predecessors)

JPEG-2000 : March 2000, by ISOITU-T H.323 and ITU-T H.324: the provision of multimedia communications over packet-switched and circuit switched networks

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Redundancies?

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Video redundanciesStatistical:

the likelihood of occurrence of intensity levels within the video sequence

Spatial:similarities of luminance and chrominance values within the same frame

Temporal:similarities encountered amongst consecutive video frames

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Video compressionThe process of removing these redundancies from the video content for the purpose of reducing the size of its digital representationQ: Any constraint on this process?

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CompressionWe already know “video redundancies”Compression = removing redundanciesWhat will be YOUR video compression techniques / algorithm?

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Evolution1st generation:

canonical pixel-based coders 2nd generation:

segmentation-based fractal-based model-based coders

3rd generation:content-based coders

[next gen?]

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Typical video encoder and decoder

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More efficient coder: if some undesired features of the input frames are primarily suppressed or enhanced (exp: noise filtering), Decoder: post-processing image enhancement techniques (exp: edge-enhancement, deblocking artefact suppression)

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converts the pixels to a different space domainExp: DCT, Waveletto eliminate the statistical redundancies

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each one of the transformed pixels is assigned a member of a finite set of output symbolsIrreversible degradation

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assigns code words to the quantized and transformed video dataUsually lossless coding techniques: Huffman, arithmetic , etc.

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the bit rate generated by video coders is highly variable, due to:

the temporal activity of video signals the variable-length coding employed in video compression scenarios

real-time transmissions smoothing bufferfeedback control mechanism