图书介绍

基于小波域隐马科夫模型的图像去噪2025|PDF|Epub|mobi|kindle电子书版本百度云盘下载

廖志武著著
出版社：成都：电子科技大学出版社
ISBN：7811141159
出版时间：2006
标注页数：206页
文件大小：51MB
文件页数：216页
主题词：小波分析－应用－图像处理

PDF下载

点此进入-本书在线PDF格式电子书下载【推荐-云解压-方便快捷】直接下载PDF格式图书。移动端-PC端通用
种子下载[BT下载速度快]温馨提示：（请使用BT下载软件FDM进行下载）软件下载地址页直链下载[便捷但速度慢] [在线试读本书] [在线获取解压码]

点击复制MD5值：4695f48c85884c920bf44033d8d94ba9

下载说明

基于小波域隐马科夫模型的图像去噪PDF格式电子书版下载

下载的文件为RAR压缩包。需要使用解压软件进行解压得到PDF格式图书。

点击复制85GB完整离线版磁力链接到迅雷FDM等BT下载工具进行下载详情点击-查看共享计划

建议使用BT下载工具Free Download Manager进行下载,简称FDM(免费,没有广告,支持多平台）。本站资源全部打包为BT种子。所以需要使用专业的BT下载软件进行下载。如BitComet qBittorrent uTorrent等BT下载工具。迅雷目前由于本站不是热门资源。不推荐使用！后期资源热门了。安装了迅雷也可以迅雷进行下载！

（文件页数要大于标注页数，上中下等多册电子书除外）

注意：本站所有压缩包均有解压码： 点击下载压缩包解压工具

图书目录

Chapter 1 Introduction1

1.1 Motivation2

1.2 Outline of Book5

1.3 Original Contributions7

Chapter 2 Wavelet and Hidden Markov Model(HMM)10

2.1 Wavelet Analysis11

2.1.1 Integral Wavelet Transform11

2.1.2 Discrete Wavelet Transform13

2.1.3 Multiresolution Analysis(MRA)of L2(R)14

2.1.4 Wavelet Packet22

2.1.5 Two Dimensional Wavelets23

2.2 Hidden Markov Model28

2.2.1 From Markov Process to Markov Model28

2.2.2 Elements of an Hidden Markov Model32

2.2.3 The Three Basic Problems for HMM34

2.2.4 Solution to Problem 1：Probability Evaluation36

2.2.5 Solution to Problem 2："Optimal"State Sequence38

2.2.6 Solution to Problem 3：Parameter Estimation40

2.2.7 Continuous Observation Densities in HMMs45

Chapter 3 Image Denoising on Wavelet Domain48

3.1 Introduction48

3.2 Important Statistical Preparations51

3.2.1 Prior and Posterior Distribution52

3.2.2 Markov Random Field54

3.2.3 Maximum Likelihood Estimate56

3.2.4 Expectation-Maximization(EM)58

3.3 Description of Image Denoising60

3.3.1 Gaussian White Noise61

3.3.2 Signal and Noise Ratios73

3.3.3 Criteria77

3.4 Wavelet Thresholding78

3.4.1 Hard and Soft Thresholding79

3.4.2 Improvements of Wavelet Thresholding80

3.5 Least Square Estimation85

3.6 Spatial Image Denoising90

3.6.1 New Frameworks93

3.6.2 Denoising Results96

3.7 Summary110

Chapter 4 Spatial Wavelet Domain Hidden Markov Model111

4.1 Preparations112

4.1.1 Statistical Models and Wavelet112

4.1.2 Gaussian Mixture Model115

4.1.3 EM Algorithm120

4.1.4 Least Square Estimation on Wavelet Domain125

4.2 Wavelet Domain-Hidden Markov Models126

4.2.1 Independent Mixture(IM)Model126

4.2.2 Hidden Markov Tree(HMT)Model127

4.2.3 Contextual Hidden Markov Model(CHMM)133

4.3 Spatial Wavelet Domain-Hidden Markov Models137

4.3.1 Gaussian Markov Field138

4.3.2 Block139

4.3.3 Template144

4.3.4 EM Algorithm of the Block HMM148

4.3.5 EM Algorithm of the Template HMM150

4.3.6 Some Views about Improved WD-HMM151

Chapter 5 Signal Denoising Using the Block HMM154

5.1 Signal Denoising156

5.2 The Signal Denoising Algorithm Using the Block HMM159

5.3 Experimental Results and Discussion165

5.4 Conclusions171

Chapter 6 Image Denoising Using the Template HMM173

6.1 Image Denoising175

6.2 The Image Denoising Algorithm Using the Template HMM180

6.3 Experimental Results and Discussion186

6.4 Conclusions193

Chapter 7 Conclusions and Perspectives195

Bibliography199