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Understanding Multimedia Data Types and Compression Techniques

This overview provides essential insights into multimedia data types, including audio, image, and video. It explains basic compression techniques necessary for efficient data storage and transmission. Key concepts such as sampling, quantization, and coding are explored, detailing how higher quality correlates with increased sampling rates and bits per sample. The content also addresses various compression methods, including lossless and lossy techniques like entropy and source encoding. Understanding these principles is crucial for effective multimedia handling and ensures optimal quality with manageable data rates.

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Understanding Multimedia Data Types and Compression Techniques

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  1. CIS679: Multimedia Basics • Multimedia data type • Basic compression techniques

  2. Multimedia Data Type • Audio • Image • Video

  3. Audio • Digitization • Sampling • Quantization • Coding • Higher sampling rate -> higher quality • Nyquist sampling theorem: for lossless digitization, the sampling rate should be at least twice the maximum frequency responses • Higher bits per sample -> higher quality • Sampling at 8 KHz, 8 bit samples -> 64kbits/sec • CD-quality audio • Sampling at 44.1KHz, 16 bit samples -> 705.6 kbits/sec

  4. Image/Video • Digitization • Scan a picture frame • Digitize every pixel • Color represented by RGB • Normally converted to Y (black and white TV), U and V • Luminance Y = 0.30R + 0.59G + 0.11 R • Chrominance U = (B-Y) * 0.493 V = (R-Y) * 0.877

  5. Video Transmission Standards • NTSC • Y = 0.30R + 0.59G + 0.14B • I = 0.60R + 0.28G + 0.32B • Q = 0.21R + 0.52G + 0.21B • PAL

  6. Studio-quality TV • NTSC • 525 lines at 30 frames/second • Y sampled at 13.5 MHz, Chrominance values at 6.75 MHz • With 8-bit samples, • Data rate = (13.5 + 6.75 + 6.75) * 8 = 216 Mbps

  7. Summary of Multimedia Data Types • Audio data rate = 64kbps, and 705.6kbps • Video date rate = 216 Mbps • Compression is required!

  8. Can Multimedia Data Be Compressed? • Redundancy can be exploited to do compression! • Spatial redundancy • correlation between neighboring pixels in image/video • Spectral redundancy • correlation among colors • Psycho-visual redundancy • Perceptual properties of human visual system

  9. Categories of Compression • Lossless • No distortion of the original content • Used for computer data, medical images, etc. • Lossy • Some distortion • Suited for audio and video

  10. Compression Techniques

  11. Entropy Encoding Techniques • Lossless compression • Run-length encoding • Represent stream as (c1, l1), (c2, l2),…, (ck, lk) • 1111111111333332222444444 = (1, 10) (3, 5) (2,4) (4, 5) • Or ABCCCCCCCCDEFGGG = ABC!8DEFGGG • Pattern Substitution • Substitute smaller symbols for frequently used patterns

  12. Huffman Coding • Use variable length codes • Most frequently used symbols coded with fewest bits • Codes are stored in a codebook • Codebook transferred with the compressed stream

  13. Source Encoding Techniques • Transformation encoding • Transform the bit-stream into another domain • Data in the new domain more amenable to compression • Type of transformation depends on data • Image/video transformed from time domain into frequency domain (DCT)

  14. Differential/Predictive Encoding • Encoding the difference between actual value and a prediction of that value • Number of Techniques • Differential Pulse Code Modulation (DPCM) • Delta Modulation (DM) • Adaptive Pulse Code Modulation (APCM) • How they work? • When consecutive change little • Suited for audio and video

  15. Vector Quantization • Divide the data stream into blocks or vectors • One or two dimensional blocks • Use codebooks • Find the closest symbol in codebook for a given sample • Transmit the reference to that symbol • Codebook present at sender/receiver • When no exact match, could send the error • Lossy or lossless • Useful with known signal characteristics • Construct codebooks that can match a wide range of symbols

  16. Major Steps of Compression • Preparation • Uncompressed analog signal -> sampled digital form • Processing • Source coding • DCT typically used: Transform from time domain -> frequency domain • Quantization • Quantize weights into integer codes • Could use different number of bits per coefficient • Entropy encoding • Lossless encoding for further compression

  17. Conclusion • Multimedia data types • Why multimedia can be compressed? • Categories of compression • Compression techniques • Entropy encoding • Source encoding • Hybrid coding • Major steps of compression • What’s next? • JPEG • MPEG

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