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A Research on Multi-Source Image Fusion and Flow Modeling

Author: ZhangQiang
Tutor: ZhouHaiYin
School: National University of Defense Science and Technology
Course: Mathematics
Keywords: Image Fusion Process modeling Algorithm is preferred Wavelet Transform Local variance High-pass filter Evaluation criteria
CLC: TP391.41
Type: Master's thesis
Year: 2007
Downloads: 180
Quote: 1
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Abstract


An important branch of the field as a multi-source data fusion, multi-source image fusion research is how the image data obtained by the different types of sensors, using a certain algorithm to its advantage or complementary organic combine to produce a new image technology. Its advantage is not only able to overcome the limitations of the single image in terms of geometry, spectral and spatial resolution and difference, thereby improving the quality of the image; but is conducive to locate targets of interest, such as identification and change detection. In today's highly developed information technology, multi-source image fusion technology has become indispensable in the field of data fusion technology, and has important applications in many military and civilian aspects. The establishment of a multi-source image fusion mechanism contains three basic elements: a reasonable image fusion process, the choice of the effective fusion rules and fusion performance evaluation. Of this research work is carried out for these three basic elements, the main work is as follows: an in-depth discussion of the different levels and modes of multi-source image fusion, multi-source image fusion method based on the pixel-level spatial domain and transform domain Classification of fusion experiments and analysis, and on this basis, the fusion of the applicability of the method and its boundary conditions; existing fusion results of evaluation methods to summarize, based on the amount of information summarized on this basis, fusion results evaluation based on statistical characteristics based on the signal-to-noise ratio, based on the gradient value of four categories of twelve, which provide a quantitative evaluation criteria for the fusion performance assessment; subjective visual analysis mainly to objective quantitative analysis, supplemented the multifactorial image fusion quality evaluation method, the closed-loop evaluation system framework, provide theoretical support for follow-up studies; 3 through the analysis of various image fusion and fusion type, multi-source image fusion process built molding method, an image data source for the entrance, as the core fusion model and integration rules, image fusion output multifactorial comprehensive criteria for evaluation of image fusion system for the end of the closed-loop image fusion process Finally, through the fusion experiment to verify the validity of the model; 4 wavelet transform image fusion based on local variance fusion rules and high-pass filtering the advantages and disadvantages of each, the choice of a new fusion rules, wavelet transform image fusion algorithm based on local variance and a high-pass filter, and full-color images and multispectral image fusion experiment, the integration of the results of the performance evaluation show that the algorithm is effective, the results of image fusion retained multi The spectral characteristics of the spectral image, and at the same time with high spatial detail.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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