电子科技大学：《图像处理及应用 Image Processing and Application》课程教学资源（课件讲稿）Chapter 08 Image Compression

电子科枝女学光电科学与工程学院 SCHOOL OF OPTOELECTRONIC SCIENCE AND ENGINEERING OF UESTC Chapter08 mage Compression Ping Zhang

Ping Zhang

电子科发女学光电科学与工程学院 SCHOOL OF OPTOELECTRONIC SCIENCE AND ENGINEERING OF UESTC Outline ◆ Background ◆Fundamentals Some Basic Compression Methods Digital Image Watermarking' 河

Outline  Background  Fundamentals  Some Basic Compression Methods  Digital Image Watermarking*  Background  Fundamentals  Some Basic Compression Methods  Digital Image Watermarking*

电子科发女学光电科学与工程学院 SCHOOL OF OPTOELECTRONIC SCIENCE AND ENGINEERING OF UESTC Outline ◆ Background ◆Fundamentals Some Basic Compression Methods Digital Image Watermarking' 河

Outline  Background  Fundamentals  Some Basic Compression Methods  Digital Image Watermarking*  Background  Fundamentals  Some Basic Compression Methods  Digital Image Watermarking*

电子科发女学光电科学与工程学院 SCHOOL OF OPTOELECTRONIC SCIENCE AND ENGINEERING OF UESTC 8,1 Fundamentals Agenda g Coding Redundancy g Spatial and Temporal Redundancy Irrelevant Information g Measuring Image Information Fidelity Criteria Image Compression Models Image Formats,Containers,and Compression Standards Agenda

 Coding Redundancy  Spatial and Temporal Redundancy  Irrelevant Information  Measuring Image Information  Fidelity Criteria  Image Compression Models  Image Formats, Containers, and Compression Standards Agenda 8.1 Fundamentals

电子科枝女学光电科学与工程学院 SCHOOL OF OPTOELECTRONIC SCIENCE AND ENGINEERING OF UESTC 8,1 Fundamentals ● The term data compression refers to the process of reducing the amount of data required to represent a given quantity of information ·Data≠Information Various amount of data can be used to represent the same information Data might contain elements that provide no relevant information data redundancy

8.1 Fundamentals • The term data compression refers to the process of reducing the amount of data required to represent a given quantity of information • Data Information • Various amount of data can be used to represent the same information • Data might contain elements that provide no relevant information : data redundancy 