【作者】 吴艳；

【导师】 杨万海；

【作者基本信息】 西安电子科技大学 ， 电路与系统， 2003， 博士

【摘要】 多传感器数据融合理论研究和应用的目标是将来自多信息源的数据和信息加以智能化的合成，产生比单一传感器更精确、更完整、更可靠的描述和判决，它在军事和民用方面有着极为广泛的应用背景，是目前科技界的一个热门研究领域。本文围绕着数据融合的三个层次：像素级融合、特征级融合和决策级融合，深入研究了多传感器图像融合、彩色纹理图像分析和雷达组网探测系统，并提出了一系列新的思想和方法，取得了良好的效果，主要内容如下：* 针对à trous小波融合方法中存在的叠加融合问题，提出了一种新的基于à trous算法的多光谱与高分辨率图像融合方法。该方法首先在à trous小波多分辨分解基础上建立了分区域融合的思想，并用进化策略成功地解决了区域划分中阈值如何确定的问题，然后提出并证明了一个有效的融合因子。融合实验表明：该方法优于IHS变换法和à trous小波融合法。* 针对Mallat小波融合方法中存在的问题，提出了一种新的基于Mallat算法的多光谱与高分辨率图像融合方法。该方法通过融合因子有效地将高分辨率图像经小波分解的低频分量信息融合到多光谱图像经小波分解的低频分量中去，实现了对已有Mallat小波融合方法的改进。* 详细地分析了拉普拉斯塔形分解的图像融合方法和Mallat算法的小波图像融合方法中存在的问题和缺点，提出了一种基于小波分解和进化策略相结合的多聚焦图像融合方法。该方法的优越之处在于充分地利用了移不变小波分解所呈现的多尺度、多方向的冗余信息，克服了Mallat小波融合法中的移变性缺点，避免了融合图像重构所带来的振铃效应。* 在灰度级纹理图像分析的基础上，研究了彩色空间转换，提出了一种基于不完全树型小波分解多特征融合的彩色纹理特征提取方法。它更全面、准确地刻画出彩色纹理的颜色特征、纹理特征及颜色与纹理的空间相关特征；同时在特征级融合基础上，针对3种不同的小波分解，研究了彩色纹理图像的分类性能及抗噪能力比较，得出不完全树型小波分解基础上的特征级融合及分类是我们的首选方案。* 针对雷达组网探测系统，将软阈值决策小波域滤波算法用于非平稳雷达回波的噪声抑制，并将此算法与多传感器并行分布式检测融合系统有机地结合在一起，提出了N-P准则下融合规则和局部判决规则之间相互关系的理论分析方法。仿真实验表明：综合算法的实现明显提高了雷达探测系统的检测性能。更多还原

【Abstract】 Study and application of multisensor data fusion theory have aimed to combine multiple source information from various sensors intelligently and obtain more detailed, complete, dependable description and decision than a single sensor. Application of multisensor data fusion span a broad range that includes military and civilian. Multisensor data fusion is one popular research field in domestic and foreign scientific and technological circles. This dissertation deeply deals with multisensor image fusion, analysis of colored texture image, radar network detection system around the three levels of data fusion: data, feature, decision. A lot of new ideas and approaches are proposed and better results are achieved. The main contributions in this dissertation can be summarized as follows: * A new method is developed to merge a high-resolution panchromatic image and a low-resolution, multi-spectral image based on à trous algorithm. Firstly this method presents a sort of fusion idea of region division based on à trous multi-resolution wavelet decomposition. Then, the evolutionary strategy is used to solve successfully the problem how to select threshold in dividing region. Finally, an influence fusion factor is proposed and verified. The fusion results show that this method can perform better than the IHS and à trous wavelet merger methods.* A new technique is presented based on Mallat algorithm for the fusion of a high-resolution panchromatic image and a low-resolution, multi-spectral image. This method can effectively merge the high-resolution panchromatic image approximation into the multi-spectral image approximation using fusion factor by means of multi-resolution wavelet decomposition, which can make an improvement on Mallat wavelet merger method.* Image fusion methods base on Laplacian pyramid decomposition and Mallat algorithm are discussed in detail, and their shortcomings are pointed out. A new method is developed to merge two spatially registered images with differing focus points based on multi-resolution wavelet decomposition and evolutionary strategy. This method has the advantage that redundant information at multi-scale and in multi-direction can be fully used by means of shift-invariant wavelet decomposition and ringing from the final merged image reconstructed by Mallat algorithm can be overcome. Color space transforms are studied based on gray texture analysis. A new representation for color texture is proposed by effectively merging both the texture and color information in feature-level based on incomplete tree-structured wavelet decomposition(ICTSWD), which can<WP=7>* describe color-texture feature with more exact and complete. Feature-level fusion and classification can be performed on the basis of the pyramid wavelet decomposition(PWD), ICTSWD and wavelet packet decomposition (WPD). The results demonstrate that colored texture feature based on ICTSWD has better classification performance and anti-noise ability than other features based on PWD and WPD. * In radar network system, wavelet filter based on soft-threshold is combined with the parallel distributed detection fusion system with multiple sensors ideally. A theoretical analysis is presented in the sense of the Neyman-Pearson (N-P) test about the relationship between fusion rule and local decision rules in the parallel distributed detection fusion. The simulation results show that synthesize algorithm can enhance the radar detection performance remarkably.更多还原