'Huffman code' presentation slideshows

Information Theory, Statistical Measures and Bioinformatics approaches to gene expression

1.25k views • 112 slides

Discrete Maths

Discrete Maths. 241-303 , Semester 1 2014-2015. Objective introduce more unusual tree algorithms and techniques you already know about binary (search) trees. 6 . Trees. Overview. 1. Uses of Trees 2. Huffman Codes 3. (Rooted) Tree Terminology 4. Spanning Trees

1.25k views • 94 slides

Huffman code and ID3

CS 157 B Lecture 18. Huffman code and ID3. Prof. Sin-Min Lee Department of Computer Science. Data Compression. Data discussed so far have used FIXED length for representation For data transfer (in particular), this method is inefficient.

750 views • 58 slides

Huffman Codes

Huffman Codes. Drozdek Chapter 11. Objectives. You will be able to Construct an optimal variable bit length code for an alphabet with known probability for each letter occuring in a message. Huffman Code Construct a tree for decoding messages encoded in a Huffman code.

702 views • 44 slides

Compression & Huffman Codes

Compression & Huffman Codes. Nelson Padua-Perez William Pugh Department of Computer Science University of Maryland, College Park. Compression. Definition Reduce size of data (number of bits needed to represent data) Benefits Reduce storage needed

404 views • 30 slides

Is ASCII the only way?

Is ASCII the only way?. For computers to do anything (besides sit on a desk and collect dust) they need two things: 1. PROGRAMS 2. DATA. A program is a set of instructions that specify each step the computer should take to solve a problem or perform a task.

413 views • 28 slides

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.

396 views • 25 slides

Digital Video Solutions to Midterm Exam 2009 Edited by Shih-Ming Huang

Digital Video Solutions to Midterm Exam 2009 Edited by Shih-Ming Huang Confirmed by Prof. Jar-Ferr Yang LAB: 92923 R, TEL: ext. 621 E-mail: smhuang@video5.ee.ncku.edu.tw Page of MPL: http://mediawww.ee.ncku.edu.tw. 2.1.

344 views • 22 slides

Introduction to Algorithms

Introduction to Algorithms. Chapter 16: Greedy Algorithms. Greedy Algorithms. Similar to dynamic programming, but simpler approach Also used for optimization problems Idea: When we have a choice to make, make the one that looks best right now

551 views • 21 slides

Huffman Codes

Huffman Codes. Encoding messages. Encode a message composed of a string of characters Codes used by computer systems ASCII uses 8 bits per character can encode 256 characters Unicode 16 bits per character can encode 65536 characters includes all characters encoded by ASCII

355 views • 20 slides

Compression techniques.

Compression techniques. Why we need compression. Types of compression Lossy and lossless Concentrate on lossless techniques. Run Length coding. Entropy or variable length coding. Huffman coding. DCT (Discrete Cosine Transform)

620 views • 20 slides

Cached Vector Quantization.

????? ???? ????? ?????? ????:?????? ?????. Cached Vector Quantization. Introduction.

293 views • 17 slides

CSC 2300 Data Structures & Algorithms

260 views • 17 slides

CIS679: JPEG (more)

CIS679: JPEG (more). Review of JPEG More about JPEG Lab project. Review of JPEG. JPEG goals Picture Preparation Component, block, and pixel Picture Processing Shift Forward DCT Quantization Different coefficients are treated separately => quantization table. Differential Encoding.

302 views • 15 slides

Chapter 4

276 views • 15 slides

Source: IEEE Transactions on Information Forensics and Security, Vol. 2, No. 1, pp. 24-30, March

1 /13. A New Steganographic Method for Data Hiding in Microsoft Word Documents by a Change Tracking Technique. Source: IEEE Transactions on Information Forensics and Security, Vol. 2, No. 1, pp. 24-30, March 2007 Authors: Tsung-Yung Liu and Wen-Hsiang Tsai

257 views • 13 slides

Compression of Stereo Images

Compression of Stereo Images. John Hamann Vickey Yeh. Outline. Basic Algorithm Color Compression Motion Compensation Conclusion. Basic Algorithm. Discrete Cosine Transform Uniform Quantization No Quantization Tables Directly Store the DC Coefficients Huffman Code the AC Coefficients

255 views • 13 slides

Huffman Code & Heaps

Data Structure: Chapter 9. Min Chen School of Computer Science and Engineering Seoul National University. Huffman Code & Heaps. Content. Huffman Code Fixed Length Coding and Variable Length Coding Principle of Huffman Coding Huffman Tree Definition of Heaps

358 views • 12 slides

The Baseline JPEG Algorithm

244 views • 12 slides

Huffman Codes

Huffman Codes. Information coding: Most info transmission machines (computer terminal, Voyager spacecraft) use a binary code. Why? These electric signals are either present or absent at any specific time. Suppose Voyager on-board camera is sensitive to four shades of gray: White Light gray

237 views • 10 slides