CIS679: Multimedia Basics

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# CIS679: Multimedia Basics - PowerPoint PPT Presentation

CIS679: Multimedia Basics. Multimedia data type Basic compression techniques. Multimedia Data Type. Audio Image Video. Audio . Digitization Sampling Quantization Coding Higher sampling rate -&gt; higher quality

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Presentation Transcript
CIS679: Multimedia Basics
• Multimedia data type
• Basic compression techniques
Multimedia Data Type
• Audio
• Image
• Video
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
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

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