Overview of Digital Video Compression Multimedia Systems and Standards S2 IF Telkom University

Agenda 1.Background 2.Why video compression? 3.User requirement from video 4.Video coding schemes 2

Background 1.Raw video signals requires a high capacity 2.Low complexity video coding algorithms must be defined to efficiently compress video sequences for storage and transmission purposes 3

Why video compression? 1.Transmission: any network  huge bandwidth requirements 2.Raw video: 320x200 pixel; 8 bit/pixel; 25 frame/sec Bandwidth to transmit 4

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 5

Video coding technology Goals: to optimize the compression efficiency; and to meet quality of service of standard video coders Evolution novel signal compression techniques 6

Video coding selection Normally depends on the bandwidth availability and the minimum quality required Exp: Video surveillance Video call Entertainment video Telemedicine Quality  application dependent Bandwidth  bit / frame rate 7

Typical Requirements Video quality and bandwidth Complexity Synchronization Delay 8

Video Quality & Bandwidth the two most important factors Higher bit rate = better quality it 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 9

Other factors Also influence the video quality and the bit rate: frame rate number of intensity and color levels image size spatial resolution 10

Quality? perceptual quality Design metric for multimedia communication networks and applications development Via 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 11

The complexity of a video coding alg. Big-O? Common indicator = FLOPs For real-time communication applications, low cost real-time implementation of the video coder is desirable Related = power consumption 12

Synchronization Synchronization between various traffic streams must be maintained in order to ensure satisfactory performance The simplest and most common technique: buffer the received data and release it as a common playback point 13

Another approach to 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 14

Delay In 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. 15

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 16

Recommendations for universal image and video coding algorithms since 1985 by ISO and ITU 1 st image coding standard: JPEG by ISO in 1989 later by ITU-T 1 st draft of a video coding standard: MPEG-1 December 1991 by ISO for audiovisual storage on CD-ROM at 1.5— 2 Mbit/s. 17

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: 1996 for very low bit rate communications over PSTN networks at less than 64 kbit/s 18

Further works Annexes: H.263+ (1998) and H (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 ISO ITU-T H.323 and ITU-T H.324: the provision of multimedia communications over packet- switched and circuit switched networks 19

Redundancies? 20

Video redundancies Statistical: 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 21

Video compression The process of removing these redundancies from the video content for the purpose of reducing the size of its digital representation Q: Any constraint on this process? 22

Compression We already know “video redundancies” Compression = removing redundancies What will be YOUR video compression techniques / algorithm? 23

Evolution 1 st generation: canonical pixel-based coders 2 nd generation: segmentation-based fractal-based model-based coders 3 rd generation: content-based coders [next gen?] 24

Typical video encoder and decoder 25

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) 26

converts the pixels to a different space domain Exp: DCT, Wavelet to eliminate the statistical redundancies 27

each one of the transformed pixels is assigned a member of a finite set of output symbols Irreversible degradation 28

assigns code words to the quantized and transformed video data Usually lossless coding techniques: Huffman, arithmetic, etc. 29

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 buffer feedback control mechanism 30