数字图像处理第八章图像压缩(图像编码)-课件

Chapter 8 Image Compression第8章 图像压缩（图像编码）目的是减少表示数字图像的数据量。去除冗余。35年前，电视传输的带宽压缩；60C.E.Shannon等的信息理论发展成目前的国际图像压缩标准。目前，图像压缩技术被认为是一种“使能技术”（enabling technology”)。提高图像分辨率，开发新的电视标准，电视会议、RS、FAX等。Chapter 8 Image Compression8.1 基础基础数据压缩表示定量信息所需数据量的减少过程数据、信息、知识。比如，不同人讲相同的事件。数据冗余：是数字图像压缩的中心问题。这不是抽象的概念，而是可以用数学式子度量的实体：如果表示相同信息的两组数据所用的信息载体单元数量分别为n1和n2,则第一组数据的相对(第二组数据的)数据冗余RD可定义为：RD=1-1/CR (-,1)其中：CR=n1/n2,(0,)Chapter 8 Image CompressionRD=1-1/CR (-,1)其中：CR=n1/n2,(0,)当n1=n2,CR=1而RD=0，表示相对于第二组数据，第一种数据表达没有包含冗余数据。当n2n1,CR0，RD-，表示第二组数据比原始表示包含多得多得数据。这也是通常不希望出现得数据膨胀。比如CR=10，RD=0.9,表示第一组数据中有90%的数据是冗余的。Chapter 8 Image Compression数据冗余的类别数据冗余的类别 1.空间冗余2.时间冗余 3.信息熵冗余（编码冗余）4结构冗余5.知识冗余 6.视觉冗余 7.其它冗余在数字图像压缩中，在数字图像压缩中，3种基本的数据冗余是种基本的数据冗余是：编码冗余，像素间冗余，心理视觉冗余。减少其中1到多种冗余就是数据压缩 Chapter 8 Image Compression8.1.1 编码冗余编码冗余Code1的二进制平均码长为3；Code1的二进制平均码长(l2pr)为2.7；Huffman码压缩比CR=3/2.7=1.11Chapter 8 Image Compression上例压缩的原理：l2(rk)与pr(rk)成反比变长编码Code1不能使其平均码长(l2pr)最小，有编码冗余冗余。数字图像一般都有编码冗余Chapter 8 Image Compression8.1.2 像元像元间的冗余的冗余c,d直方图分别对应a,b图，相同的三峰，两边是火柴：等长码有编码冗余，可用变长码压缩。但是，变长码还是不能改变像元间的相关性。计算像元间的相关性可用P414中的6式。沿某水平线e,f分别反映a,b图像像元在不同间隔后灰度的相关程度利用像元利用像元值的空的空间相关可相关可预测Chapter 8 Image Compression减少像元间冗余像元间冗余的一种方法：行程编码行程编码(RLC)Run-Length Codeabcd,nonvisualp.417,CR的计算Chapter 8 Image Compression 8.1.3视觉冗余视觉冗余256 12864 3216 8 4 2在在8个比特的灰度个比特的灰度值中，每次去掉一个中，每次去掉一个bit面，从左面，从左/右？右？Chapter 8 Image Compression8.1.3 Psycho-visual Redundancy眼睛对所有视觉信息的响应具有不同的灵敏度。消除心理心理视觉冗余冗余会导致数量信息的损失，又称量化量化。原原图256级16级,2:1IGC16级,2:1Chapter 8 Image Compression量化,不可逆，信息损失IGS,Improved Gray-Scale quantizationIGS意意识到眼睛到眼睛对边缘特有的敏感性，通特有的敏感性，通过加入加入伪随机数随机数来破坏来破坏边缘：伪随机数从邻近像元的低伪随机数从邻近像元的低4位获得，加入当前像元灰度值后位获得，加入当前像元灰度值后才量化。才量化。（图像的低bit面很象随机数，见p.89）低4位的初值为0000，对高4位为1111的像素不加随机数。0110 1100 00000110 11001000 1011 11001001 01111000 0111 01111000 11101111 0100 11101111 0100Chapter 8 Image Compression8.1.4 保真度准保真度准则Objective/Subjective Fidelity CriteriaObjective：SNR,p.420Subjective:judged by a group of peopleObjective：Subjective=3：7Chapter 8 Image Compression8.2 Image Compression Models图8.5 通用通用压缩系系统模型模型信源信源编码：消除：消除输入冗余。入冗余。信道信道编码：对源源编码的的输出加出加强强噪声免疫。噪声免疫。Chapter 8 Image CompressionabMapper:减少空减少空间冗余冗余Quantizer:减少减少视觉冗余。冗余。不可逆，不失真（熵）编码要省去。Symbol encoder:减少减少编码冗余冗余Chapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage 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8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionTable 8.19(Cont)Chapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage CompressionChapter 8 Image CompressionChapter 8Chapter 8Image CompressionImage Compression