【作者】 戚文婷；

【导师】 张钧萍；

【作者基本信息】 哈尔滨工业大学 ， 信息与通信工程， 2010， 硕士

【摘要】 典型线目标(道路和海岸线)的提取,在军事和民用领域的各方面已获得广泛的应用,并发挥着巨大的作用。而随着遥感技术的发展,仅依靠单个光谱信息的传统分类方法难以满足实际需求,为了进一步提高信息的利用率,我们将融合思想引入到线目标的提取。利用不同数据源的信息协同处理来提高线目标识别的精准度。本论文针对多源遥感图像的特点及优势,以可见光全色图像、多光谱图像和SAR图像为数据源,以线目标(道路和海岸线)为研究对象,主要利用了新型小波(双树复小波和非下采样的Contourlet变换)融合的手段,对多源遥感图像中的线目标提取问题做了研究和分析。论文首先研究了小波和新型小波的基本理论及融合算法,深入研究了双树复小波和非下采样的Contourlet变换的性质及特点,通过实验对新型小波的性质进行了验证,并从多方向性、平移不变性和各向异性三方面进行了分析。在此基础上,提出了将双树复小波和非下采样的Contourlet变换相结合的改进融合算法,通过优势互补,提高了融合后图像对边缘和细节的保持能力。该方法可以使融合后的图像的线特征更加明显,便于后续线目标的提取。然后,研究了基于融合的道路和海岸线目标提取方法。针对不同数据源特点,采用不同的道路预处理方法,并提出了一种基于数学形态学和局部Hough变换的道路融合提取算法。采用“提取—融合—后处理”流程完成了对道路目标提取的整个过程。通过实验证明,该算法对于不同分辨率和不同信源的图像,都能以较高的精确度提取出道路并有效保持其原始形状。针对海岸线,采用基于融合的分类算法进行海岸线提取,克服了分类算法对边缘保持较差的缺点,经过融合分类后,去除了大部分的干扰信息,有利于后续对海岸线的边缘检测。更多还原

【Abstract】 The extraction of typical line objects (road and coastline) is widely used not only in military reconnaissance but also in civilian use. With the development of remote sensing technology, the information from a single sensor can not fully reflect the characteristics of the target. In order to gain more information, the idea of fusion is be introduced into the extraction of line objects. Therefore, the collaborative use of the information of spatial and spectral characteristics can improve the accuracy of recognition. In this dissertation, panchromatic images, multi-spectral images and SAR images for the data source, the issue of line objects extraction in multi-source remote sensing images is researched and analyzed mainly by the use of new-type wavelet fusion(dual-tree complex wavelets(DT-CWT) and nonsubsampled contourlet transform(NSCT).Firstly, on the basis of research on wavelet, the new-typical wavelets theories is deeply studied, especially in the nature of DT-CWT and NSCT. The nature are analyzed from the multi-direction, shift invariant and anisotropy. A image fusion method based on the combination of DT-CWT and NSCT is presented. This method can make line features more obvious in the fused image, which is in favor of the following process of target extraction.Secondly, this dissertation researches the method of extracting road and coastline object which are based on fusion. In response to the features of different sources, the different pretreatment for the extraction is used. A road extraction method based on the Hough transform and mathematical morphology is presented. This method extracts roads through the " Extraction - Fusion- Aftertreatment " three steps with the primitive roads. This method can increase the precision for the extraction of road. For the coastline, an improved method for classification is used to extract coastline from the fused image. This method can get over shortcomings of classification, make line features more obvious in the image.更多还原