图像融合算法的分析与实现

Analysis and Implementation of Image Fusion Algorithm

图像融合作为多传感器信息融合的重要分支,被广泛应用于各种领域。图像融合已成为监控系统中不可分割的一部分。分析图像融合传感器的种类,图像融合算法的评价指标和图像融合算法的分类。像素级图像融合作为各级图像融合的基础,尽可能多地保留场景的原始信息,提供其他融合层次所不能提供的丰富、精确、可靠的信息,有利于图像的进一步分析与处理。研究塔式图像分解,主成分分析图像和小波图像分解融合算法,并通过MATLAB编码实现其融合算法,评价算法的性能指标。最后用小波分解算法实现一组被动红外图像和可见光图像的融合,并评价其性能。

Image fusion, as an important branch of multi sensor information fusion, is widely used in various fields. And image fusion has become an integral part of the monitoring system. Analyzes the types of image fusion sensors, the evaluation index of image fusion algorithm and the classification of image fusion algorithms. Pixel level image fusion can provide richer,more accurate and reliable information for further analysis and processing of the image. Studies the pyramid image decomposition, principal component analysis and wavelet image decom- position and fusion algorithms, and evaluates the performance of the algorithms. Finally, fuses a set of passive infrared image and visible light image by wavelet decomposition algorithm, and evaluates the performance of the algorithm.