首页--工业技术论文--自动化技术、计算机技术论文--计算技术、计算机技术论文--计算机的应用论文--信息处理(信息加工)论文--模式识别与装置论文

Efficient Algorithms of Image Fusion Based on Hybrid Techniques

ABSTRACT第5页
LIST OF ABBREVIATIONS第13-14页
CHAPTER 1 INTODUCTION AND LITERATURE REVIEW第14-25页
    1.1 Research Background第14-16页
        1.1.1 Introduction第15页
        1.1.2 Motivation第15-16页
    1.2 Research Problem第16页
        1.2.1 Aims and Objectives of Thesis第16页
        1.2.2 Scope of thesis第16页
    1.3 Literature Review第16-25页
        1.3.1 Definition of an Image第16-17页
        1.3.2 Definition of Image Fusion第17-18页
        1.3.3 Categories of Image Fusion第18页
        1.3.4 Multi-view Fusion第18页
        1.3.5 Multimodal Fusion第18页
        1.3.6 Multi-Temporal Fusion第18-19页
        1.3.7 Classification of Image Fusion第19页
        1.3.8 Image Fusion System Using Single Sensor第19-20页
        1.3.9 Image Fusion System Using Multiple Sensor第20页
        1.3.10 Super-resolution Image Reconstruction第20页
        1.3.11 Image Fusion Scheme Using ICA Bases第20-21页
        1.3.12 Region Based Multi-Focus Image Fusion第21页
        1.3.13 Fusion Techniques for Non-Destructive Testing and Remote Sensing第21-22页
        1.3.14 Multi-Resolution Pyramidal Image fusion第22-23页
        1.3.15 Wavelet Transform Based Image Fusion Algorithm第23-24页
        1.3.16 Applications of Image Fusion第24-25页
CHAPTER 2 METHODS OF IMAGE FUSION第25-33页
    2.1 Techniques of Image Fusion第25-26页
        2.1.1 Spatial Domain Fusion Method第25页
        2.1.2 Transform Domain Fusion Method第25-26页
    2.2 Spatial Domain Techniques第26-28页
        2.2.1 Simple Average Image Fusion Technique第26页
        2.2.2 Select Maximum Based Image Fusion Technique第26-27页
        2.2.3 IHS Image Fusion Technique第27页
        2.2.4 Principal Component Analysis (PCA)第27-28页
    2.3 Transform Domain Techniques第28-33页
        2.3.1 Discrete Orthogonal Wavelet Decomposition Technique第28-29页
        2.3.2 Curve-let Transform Based Image Fusion Technique第29-30页
        2.3.3 Discrete Wavelet Transform第30页
        2.3.4 Classification of wavelets第30-31页
        2.3.5 Wavelet families第31-33页
CHAPTER 3 PROPOSED METHODS OF IMAGE FUSION第33-48页
    3.1 Algorithms for Image Fusion第33-43页
        3.1.1 Principal Component Analysis第33-36页
        3.1.2 Discrete Wavelet Transform第36-38页
        3.1.3 Image Decomposition in Discrete Wavelet Transform (DWT)第38-39页
        3.1.4 Image Reconstruction in DWT第39-40页
        3.1.5 Algorithm for Implementation of DWT第40页
        3.1.6 Discrete Stationary Wavelet Transform第40-42页
        3.1.7 Inverse Discrete Stationary Wavelet Transform第42-43页
        3.1.8 Algorithm for Implementation of DSWT第43页
    3.2 Proposed Algorithm第43-48页
        3.2.1 PCA+DWT Combined Algorithm第43-44页
        3.2.2 Algorithm for Implementation of PCA+DWT第44-45页
        3.2.3 PCA+DSWT Combined Algorithm第45-47页
        3.2.4 Algorithm for Implementation of PCA+DSWT第47-48页
CHAPTER 4 QUALITY PARAMETERS OF IMAGE FUSION WITH RESULTS AND DISCUSSIONS第48-57页
    4.1 Performance Parameters第48页
        4.1.1 Sharpness第48页
        4.1.2 Noise第48页
        4.1.3 Colour Accuracy第48页
        4.1.4 Distortion第48页
        4.1.5 Artifacts第48页
    4.2 Classification of Image Quality Parameters第48-51页
        4.2.1 Mean Squared Error第49页
        4.2.2 Peak Signal to Noise Ratio第49页
        4.2.3 Normalized Cross Correlation第49-50页
        4.2.4 Maximum Difference第50页
        4.2.5 Entropy第50页
        4.2.6 Average Difference第50-51页
        4.2.7 Structural Content第51页
    4.3 Purpose of Developing Algorithm第51-52页
    4.4 Simulation Results第52-57页
        4.4.1 Scenario-01第53-55页
        4.4.2 Scenario-02第55-57页
CHAPTER 5 CONCLUSIONS AND FUTURE RECEOMMENDATIONS第57-58页
    5.1 Conclusions第57页
    5.2 Future Recommendations第57-58页
BIBLIOGRAPHY第58-62页
ACKNOWLEDGEMENT第62-63页
附件第63页

论文共63页,点击 下载论文
上一篇:支持多关键字可排序的高性能可搜索加密系统及其应用
下一篇:基于依存树和注意力的属性级别情感分类研究