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Introduction to Multimedia Data Compression

Introduction to Multimedia Data Compression. DSP Research and Technology IURC Microelectronics ITB. Contents. Introduction: Compression Objectives Multimedia: System and Applications Digital Media Voice Music Image Video Compression Basic Principles Multi Media Compression Standards

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Introduction to Multimedia Data Compression

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  1. Introduction to Multimedia Data Compression DSP Research and Technology IURC Microelectronics ITB

  2. Contents • Introduction: Compression Objectives • Multimedia: System and Applications • Digital Media • Voice • Music • Image • Video • Compression • Basic Principles • Multi Media Compression • Standards • What Next? Future Technology MPEG-7, Emotion Digitization

  3. Multimedia Compression Objectives • Primary Objectives • To use digital bits efficiently for representing multimedia signals effectively • Multimedia signals • Speech, audio/music, images, video, dll • Applications • Communications, Internet, Broadcasting, Storage

  4. Multimedia Technology It’s importance

  5. Multimedia: ART Joins BRAIN Merging of advanced digital and analog technology Analog Domain Digital Domain Analog or Real-World Signals Digital or Computer-World Signals Analog Signal Processing Digital Signal Processing A/D D/A Converter Technology Provides the Bridge [ICE 1997]

  6. Three Types of Contents: Control, Information, and Media Low Bitrate Error Intolerant (Intermittent) Control (Automation, Interaction, Instruction) D NS Information (Database, WEB) IP PS Medium Bitrate Error Disliked (Burst) Media (Speech, Music, Image, Video) CS MPLS High Bitrate Error tolerant (Stream) Evolution trends

  7. Media Access Information Infrastructure Private IP IP Cloud Leased Lines CDMA/GSM PSTN Transmux User Services Billing Media Channel Control Channel Information Channel Control/ Gatekeeper Media Switch Info Switch Gateway Local Info Server Local Media Server Transmux Analog Phone + V34 WLL WLAN Ethernet RS232/ RS422 Fiber Powerline Users

  8. Multimedia Systems • Text • Graph • Speech • Audio • Video A technology of use and integration of different media, such as

  9. Multimedia System Cores Computing Communications System/ Integration SignalProcessing

  10. Education Health Care Consumer Electronics Geographical IS Navigational Systems Business and Finance High Quality Communications Digital Libraries Entertainment Telecommuting Publishing Virtual Reality Commercial Electronics Cooperation Applications [Gray97]

  11. Education • Information Access • Teaching Tools • Interactive Teaching • Distance Learning

  12. Health Care • Biomedical data acquisition, transmission, storage, interpretation • Diagnosis aids • Tele medicine

  13. Collaboration Environment

  14. Media Processing and Integration • Text and Graph Compression • Speech, audio, image, and video processing and coding • Joint audio visual coding • Hypermedia, 3D, VR processing

  15. Multimedia System Design and Implementation • Parallel DSP architecture • ASIC design • DSP Software and hardware design • Sound and Display devices and peripherals • Storage technology • System integration

  16. Application Developers • Design houses • Software developers • Applications market systems Multimedia House

  17. Media Digitalization Converting Media Into Bits

  18. Digital Media System Diagram • A/D converter converts multimedia signals into digital bit • Digitalbits are digital representation of the media signals • Compression Encoder reduces the number of representation bits without eliminating media contents • Bitstream is highly-compacted digital bits as the compression results • Compression Decoder reconstructs digital bits back from the bitstream • D/A converter converts digital bits into multimedia signal

  19. Analog Signal xa(t) A Acos t A: Amplitude : Frequency (Radian) F: Frequency (Hertz) : Phase

  20. Digital Signal x(n) A Acos n A: Amplitude : Frekuency (Radian) f: Frequency : Phase

  21. Analog-Digital Conversion Analog Signal • Sampling, with Fs = 1/T • Quantization • Coding Filter Bandlimited Signal Sampling Discrete Time Quantization Discrete Valued Coding Digital

  22. Sampling of Sinusoids Suppose there is an analog signal being sampled If sampling frequency Fs= 1/T, we obtain Thus there is a linear relationship f = F/Fs or w = WT f Folding Frequency 1/2 F 0.5Fs Fs -1/2

  23. Sampling Theorem To reconstruct analog signals having maximum frequency Fmax = B while Fs > 2 Fmax, use sinc interpolator: Fn = 2 Fmax is called Nyquist rate. - Sampling frequency must exceed Nyquist rate. - If sampling frequency cannot be increased, Fmax must be lowered with an anti-aliasing filter.

  24. Quantization Amplitude • Quantisation Error eq(n) = xq(n)-x(n) • Is limited by resolution D -D/2 eq(n) D /2 • Resolution improves is the number of quantization level L increases while dynamic range (xmax-xmin) decreases: D=dynamic range /(L-1) • L = 2b, where b is the number of bits per sample • Total bit = b x Fs • Signal-to-Noise Ratio (SNR dB) = 10 log( Signal Energy / Distortion Energi) • SNR is about 6 x b dB xq(n) xmax D xa(t) xmin n Quantization levels

  25. Applications On Digital Speech • Speech signal from a microphone • filtered (anti aliasing) 300Hz – 3300 Hz • sampled at 8000 samples per second • Quantization resolution is 8 bits per sample. • Resulting digital speech data: • Bit rates needed: 8000 x 8 = 64 kbps • Quality: SNR about 48 dB

  26. Applications on Audio / Music • Audio signal from audio source (microphone, audio out) • filterered (anti aliasing) 0Hz – 20000 Hz • sampled 44100 at samples per second • quantisation at 16 bit per sample resolution • has two channels L-R stereo • Resulting digital audio data: • Bit rates: 44100 x 16 x 2 = 1,411,200 bps = about 1.4 Mbps • Quality: SNR about 96 dB

  27. Digital Image • In contrast with speech and music, an image signal is known as an intensity signal at a two dimensional domain. Marco: 294x383, 24 bpp, colour, 331 KBytes

  28. Sampling of Digital Image

  29. Interlaced vs Progresive Scan

  30. Color Table • Color Table is a code mapping indices with certain color • Every picture sample (pixel) contains an index (in bits) of Color Table • More bits per index results in richer possible color, but in effect increases bits required per image

  31. Additive Color RGB Magenta White Blue Red Cyan Yellow Green

  32. RGB Images 24 bpp RGB 8 bpp Red Component 8 bpp Blue Component 8 bpp Green Component

  33. Hue-Saturation-Brightnes A. Saturation B. Hue C. Brightness D. All hues

  34. Alternative to RGB: Y-C1-C2 • Colour image can be represented by three ‘8 bpp’ images: R, G, B. • Alternatively, one can use three ‘8 bpp’ images: Luminance Y, Chrominance 1 (C1), and Chrominance 2 (C2) • NTSC, PAL, and Secam use similar Luminance but slightly different Chrominance

  35. Color Picture Sizes

  36. RGB-NTSC Color Converter • Conversion • : Y = 0.299 R + 0.587 G + 0.114 B • : I= 0.596 R – 0.274 G – 0.322 B • : Q = 0.211 R – 0.523 G + 0.311 B • Inversion • : R = Y + 0.956 I + 0.621 Q • : G = Y – 0.272 I – 0.649 Q • : B = Y – 1.106 I + 1.703 Q

  37. RGB-PAL Color Converter • Conversion • : Y = 0.299 R + 0.587 G + 0.114 B • : U= – 0.148 R – 0.289 G + 0.437 B • : V = 0.615 R – 0.515 G – 0.100 B • Inversion • : R = Y + 1.14 V • : G = Y – 0.394 U – 0.581 V • : B = Y + 2.032 U

  38. RGB-SECAM Color Converter • Conversion • : Y = 0.299 R + 0.587 G + 0.114 B • : Db= – 0.450 R – 0.833 G + 1.333 B • : Dr = – 1.333 R + 1.116 G – 0.217 B • Inversion • : R = Y – 0.526 Dr • : G = Y – 0.129 Db + 0.268 Dr • : B = Y + 0.665 Db

  39. YUV Example 24 bpp Original 8 bpp Y Component 8 bpp V Component (offset by 0.5) 8 bpp U Component (offset by 0.5)

  40. Color Needs Many Bits 8 bpp greyscale 66 KBytes 1 bpp Monochrome 9 KBytes 24 bpp colour, 193 KBytes 8 bpp Custom Color 66 KBytes Marco 256 x 256

  41. Size Factor Marco: 256x256, 24 bpp, colour, 193 KBytes Marco: 294x383, 24 bpp, colour, 331 KBytes

  42. Number of Samples Factor 64x64 12,344 bytes 32x32 3,148 bytes 16x16 824 bytes 8x8 248 bytes

  43. Comparison of Spatial Resolution

  44. Digital Video Signal 3 5 7 9 Time Index 11 Time Index 1 • Digital video signal is a collection of digital images (called frames) that is ‘displayed’ in sequence with respect to time index.

  45. Frames Per Second Factor • Increasing frame per second (fps) improves transition smoothness such that images become alive. However that increases required number of bits. • Typical fps are 5 fps, 30 fps, dan 60 fps, for videophone, TV, and HDTV

  46. Digital Video Signal

  47. Digital Video Structure

  48. Macroblocks and YUV File

  49. Compression of Media Bits Saving Bits For Multimedia

  50. Compression: Bit Savings

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