預測編碼與變換編碼在圖像壓縮中的應用與分析

信息計算科學論文編號:XXLW011 論文字數:10130,頁數:30  附任務書,開題報告,文獻綜述，外文翻譯

目錄
封面........................................................................i
中文摘要....................................................................ii
英文摘要....................................................................iii
概述.................................................................1
 1.1 圖像壓縮的意義.....................................................1
 1.2 圖像壓縮技術分類...................................................2
 1.3 預測編碼與變換編碼概述.............................................3
第二章 預測編碼..............................................................5
      2.1 預測編碼原理.......................................................5
      2.2 線性預測...........................................................6
      2.3非線性自適應預測.......................... .........................8
第三章 變換編碼..............................................................12
      3.1 正交變換...........................................................12
          3.1.1連續函數集合的正交性.........................................12
          3.1.2 二維離散正交變換.............................................12
          3.1.3 正交變換的物理意義...........................................14
      3.2 傅立葉變換.........................................................15
          3.2.1 一維傅立葉變換...............................................15
          3.2.2 二維傅立葉變換...............................................17
      3.3 K-L變換............................................................18
          3.3.1 K-L變換原理................................................. 18
      3.4 離散余弦變換.......................................................19
          3.4.1 離散余弦變換原理.............................................19
          3.4.2 快速DCT算法.................................................20
第四章 離散余弦變換的Matlab實現.................... ........................23
      4.1 Matlab 簡介........................................................23
      4.2 離散余弦變換的Matlab實現..........................................23
結束語.......................................................................28
致謝.........................................................................29
參考文獻.....................................................................30

摘  要
 
 在信息世界迅猛發展的今天,人們對計算機實時處理圖像信息的要求越來越高。如何在保證圖像質量的前提下,同時兼顧實時性和高效性成了一個值得關注的問題。于是,對圖像信息進行一定的壓縮處理成為了一個不可或缺的環節。圖像壓縮是關于用最少的數據量來表示盡可能多的原圖像的信息的一個過程。
    本文主要研究圖像壓縮編碼理論，包括兩個部分內容：編碼技術和編碼流程。在編碼技術中，我們詳細介紹了預測編碼、DCT變換編碼、數據量化、熵編碼的原理及其在圖像壓縮中的應用。預測編碼減弱了圖像數據的時間相關性；DCT變換編碼減弱了數據的空間相關性；數據量化利用了人眼心理視覺冗余；熵編碼減小了編碼冗余。減小了這些冗余，圖像數據將得到有效的壓縮。
　　在編碼技術基礎之上，系統地討論了運動圖像視頻序列的編碼流程，包括幀內編碼模式和幀間編碼模式。其中重點研究了運動補償幀間預測結合DCT變換的幀間壓縮編碼，分析了運動補償的原理和運動矢量的計算方法。

關鍵詞 正交變換;圖像壓縮;快速DCT算法;Matlab

A Deep Analysis of Similarities And Predictive Coding And Transformation Coding

Abstract

 Today,information industry is developing swift and violent,people of real-time computer image information processing increasingly high demands. How to guarantee the quality of the image,taking into account real-time performance and efficiency has become a matter of concern. Thus,processing compression and disposal of the image information will be an indispensable link. Image compression is a process of the least amount of data to show as many as possible of the original image information.
　　traditional methods and the use of those methods in the image compression, for example estimation coding, DCT transform, data quantization, entropy coding. Estimation coding lowers the time relativity of image data. DCT transform lowers the space relativity of image data. Data quantization makes use of the redundancy of mentality and vision . Entropy coding brings down the redundancy of coding. After those process, image data will be effectively compressed.
     Based on the coding technology, which includes frame and field coding mode. This paper particularly expounds the field coding of motion compensation combined with DCT transform, introduces the theory of motion compensation and the count of motion vector. Motion compensation makes better use of relativity of field data and increases the compensation ratio.

Key words :orthogonal transformation;image compression;Fast Algorithm for DCT;Matlab