Outline Kinds of Coding Need for Compression Basic Types Taxonomy Performance Metrics

Two kinds of Coding of Information Source Coding: Coding for efficient representation of information. (Also called Compression)‏ Channel Coding: Coding for error free transmission of information through a noisy medium

Need for Compression Multimedia data need  Huge storage space  Large Bandwidth for transmission Storage, Bandwidth Requirements are usually much greater than availability Compression is a viable technique

Multimedia Storage/Bandwidth Requirements GB. ~922 GB. 221 Mbits/sec.60 mins. Video NTSC HDTV ~307KB. ~922KB. 640  480 Image Gray scale (8-bit) Color (24-bit)‏ 635MB. 28.8MB Mbits/lsec. 64Kbits/sec. 60 mins Audio CD-DA quality Speech quality StorageBandwidthDuration/SizeMedia type

Images and Video are usually: Generated in Analog form Captured in Analog form Processed in Digital form Stored in Analog/Digital form Transmitted in Analog/Digital form

Advantages of Digital Media Ease of processing (for noise removal, quality enhancement, etc. Robustness to error (in storage/transmission)‏ Ease of integration of discrete media

A/D Conversion Two major steps: Sampling Quantization

Compression Techniques Two kinds of compression Lossless and Lossy Compression techniques take advantage of redundancy in digital images Types of redundancies  Spatial redundancy: due to the correlation between neighboring pixel values  Spectral redundancy: due to the correlation between different color planes or spectral bands Lossy techniques, in addition, take advantage of HVS (Human Visual System) properties

Lossless and Lossy Compression Lossless Compression:  No loss of information  Original data exactly recovered from compressed data  Lower compression ratio Lossy Compression:  Loss of information  Perceptual loss of information reduced (controlled)  Higher compression ratio

Lossless Coding techniques (Entropy Coding)‏ Repetitive Sequence Encoding Statistical Encoding Lossless Predictive Coding Bitplane Encoding Taxonomy of Image Compression RLEHuffman Arithmetic LZW DPCM

Lossy Coding techniques (Source Coding)‏ Block Truncation Coding Lossy Predictive Coding DPAM ADPCM Delta modulation Transform Coding DFT DCT Haar Hadamard Subband Coding Subbands Wavelets Fractal Coding Vector quantization Taxonomy of Image Compression

Audio-visual Communications, Multimedia, Remote sensing MPEG-4 Video, HDTV, DSMMPEG-2 Video, Digital Storage Media(DSM)‏MPEG-1 TeleconferencingCCITT H.261 Facsimile, Document ImagingJBIG Photographic ImagingJPEG Facsimile, Document ImagingCCITT T.6 Facsimile, Document ImagingCCITT T.4 Possible Application AreasStandards Image Compression Standards

Performance Metrics for Lossy Techniques Compression Ratio (CR)‏ Peak Signal to Noise Ratio (PSNR)‏ RMSE is the Root Mean Square Error between the original and reconstructed data Speed (Complexity) of encoding and decoding Digital Image is a rectangular array of pixels (picture elements)‏

Summary Source Coding = Compression Compression takes advantage of redundancies Basic Types: Lossless and Lossy Compression Ratio and Quality (Fidelity) Tradeoffs