'Huffman codes' diaporamas de présentation

Image Compression

Image Compression. Chapter 8. 1 Introduction and background. The problem: Reducing the amount of data required to represent a digital image. Compression is achieved by removing the data redundancies: Coding redundancy Interpixel redundancy Psychovisual redundancy.

989 views • 80 slides

Image Compression

Image Compression. Chapter 8. 1 Introduction and background. The problem: Reducing the amount of data required to represent a digital image. Compression is achieved by removing the data redundancies: Coding redundancy Interpixel redundancy Psychovisual redundancy.

982 views • 80 slides

Information Retrieval

Information Retrieval. Data compression. Architectural features. net. L2. RAM. HD. CPU. L1. registers. Few Tbs. Few Gbs Tens of nanosecs Some words fetched. Cache Few Mbs Some nanosecs Few words fetched. Few millisecs B = 32K page. Many Tbs Even secs Packets.

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Advanced Algorithms

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ALGORITHM TYPES

ALGORITHM TYPES. Greedy, Divide and Conquer, Dynamic Programming, Random Algorithms, and Backtracking. Note the general strategy from the examples. The classification is neither exhaustive (there may be more) nor mutually exclusive (one may combine).

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4C8 Dr. David Corrigan

4C8 Dr. David Corrigan. Jpeg and the DCT. 2D DCT. DCT Basis Functions . 2D DCT. Q step = 15. Each band is the same size and there are 64 bands in total so the entropy is. Optimum Block Size is 8!. Slow DCT. Sledgehammer implementation for 8 point DCT

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Algorithms for Data Compression

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Algorithms for Data Compression

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Algorithms for Data Compression

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compress!

prob. 0.512 0.128 0.128 0.032 0.128 0.032 0.032 0.008. cdwd 0 100 101 11100 110 11101 11110 11111. prob. 0.8 0.2. cdwd 0 1. AAA AAB ABA ABB BAA BAB BBA BBB. A B. compress!. From theoretical viewpoint ... block Huffman codes achieve the best efficiency.

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So far

So far. Audio (scalar values with time), image (2-D data) and video (2-D with time) Higher fidelity means more data (more quantization resolution, more pixel resolution etc.) Human physiology can help achieve better compression because of limitations of human hearing, vision etc.

395 views • 25 slides

Lossless/Near-lossless Compression of Still and Moving Images

Lossless/Near-lossless Compression of Still and Moving Images. Xiaolin Wu Polytechnic University Brooklyn, NY. Part 2. Entropy coding. Variable length codes (VLC). Map more frequently occurring symbols to shorter codewords abracadabra

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Huffman Codes

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Synchronization of Huffman codes

Synchronization of Huffman codes. Marek Biskup Warsaw University Phd-Open, 2007-05-26. 0. 1. 0. 1. 0. 1. a. 0. 1. b. c. d. e. Huffman Codes. Each letter has a corresponding binary string (its code) The codes form a complete binary tree

276 views • 14 slides

Synchronization of Huffman codes

Synchronization of Huffman codes. Marek Biskup Warsaw University Phd-Open, 2007-05-26. 0. 1. 0. 1. 0. 1. a. 0. 1. b. c. d. e. Huffman Codes. Each letter has a corresponding binary string (its code) The codes form a complete binary tree

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EE800 Term Project Huffman Coding

Abdullah Aldahami (11074595) April 6, 2010. EE800 Term Project Huffman Coding. Huffman Coding Introduction. Huffman Coding is a simple algorithm that generates a set of variable sized codes with the minimum average size. Huffman codes are part of several data formats as ZIP, MPEG and JPEG.

373 views • 11 slides