扫描地形图和遥感图像中的目标识别
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摘要
地图矢量化和遥感图像智能处理是当今学术和应用领域广为关注的热点内容，对构建现代数字地理信息和扩展其应用具有十分重要的意义。本文围绕扫描地形图和遥感图像中主要目标的提取、识别和分类问题，进行了深入系统的研究。
在地图矢量化方面，以在实际中最常使用的地形图为对象，主要研究了彩色扫描地形图中等高线和街区式居民地的自动提取。(1)提出了一种基于颜色键集合(color key set)技术的彩色地图分色改进算法，抑制了扫描图像中的颜色失真。(2)提出了一种了适合一般质量地形图中等高线自动提取的新方法，利用灰度线段分割修补等高线彩色分割结果和局部窗口分割技术，解决了等高线的断裂和粘连问题。(3)提出了先用Gabor滤波器检测晕线再提取居民地轮廓的方法，能够识别彩色地形图中街区式居民地。(4)研制了一个地形图矢量化软件——AutoVector，并已得到初步应用。
在遥感图像智能处理方面，主要研究了高分辨率全色遥感图像和多光谱遥感图像中纹理特征提取，以及目标检测与分类。纹理特征提取研究主要包括：(1)提出了一种在高分辨率全色图像上结合Gabor小波和ICA的纹理特征提取(ICAG)方法，获得了ICAGⅠ和ICAGⅡ两种纹理特征，用于表征纹理在不同尺度和方向上的高阶统计特性。(2)提出了一个ICA多尺度纹理算子，它先利用多个波段数据建立高维矢量再通过ICA提取纹理特征用于多光谱纹理分析。目标检测与分类研究主要包括：(1)提出了一种融合基于ICAGⅡ纹理特征的区域分割和边缘检测方法，能够自动识别高分辨率全色遥感图像中城镇和乡村级居民地。(2)提出了一种组合地物的光谱特征、几何形状特征和ICA多尺度纹理算子的分层分类方法，实现了多光谱图像中盐渍土的自动分类，解决了盐渍土与农田等非盐渍土地物边界不易区分，裸露盐渍土同居民地、道路之间的光谱混淆，以及有植被覆盖盐渍土光谱特征不一致等问题。
Nowadays scanned map vectorization and intelligent processing of remote sensing images is an active area attended widely in the fields of science research and application. They play a very important role for the creation and application of digital geographic information. This thesis focuses on the automatic extraction, recognition and classification of the main objects in the scanned topographic maps and remote sensing images.
In the scanned map vectorization, the thesis mainly studies the automatic extraction of the contour lines and residential area symbols in the chromatic scanned topographic maps. (1) A color key set technique based color separation modified algorithm of chromatic maps is developed, which can restrain color distortion in the scanned maps. (2) A novel method for extracting contour lines from common-conditioned topographic maps is presented, which solves contour line disconnection and conglutination by both contour line color segmentation results repaired with the line gray segmentation and local window segmentation. (3) A method to recognize the residential area symbols in the chromatic scanned topographic maps is offered, which firstly detects hatched lines by the Gabor filter and then extracts the contours of residential area symbols. (4) The topographic map vectorization software—AutoVector is developed and has been used initially.
In the intelligent processing of remote sensing images, the thesis mainly studies texture feature extraction, object detection and classification in both high resolution panchromatic and multispectral images. The research of texture feature extraction contains: (1) a method called ICAG is proposed by combining Gabor wavelets and independent component analysis (ICA) for extracting texture features in high resolution panchromatic images. This method constructs two texture features: ICAG I and ICAG II, which can be used to characterize the higher-order statistical properties of the texture in different scales and orientations. (2) An ICA based multiscale texture operator is presented, which firstly makes use of multiple bands data to construct the vectors with high dimensionality and then extracts features by ICA from these vectors for multispectral texture analysis. The research of object detection and classification contains: (1) a method for recognizing towns and villages in high resolution panchromatic images is presented by fusing area segmentation based on the ICAG II texture features and edge detection. (2) A layered classification method for saline soils classification in multispectral images is proposed by combining the spectral feature, the geometric feature and the ICA based multiscale texture operator. This method solves the problems, such as the edges among saline soils and other non-saline soils are difficult to be distinguished, bare vegetation saline soils have similar spectra to that of populated areas and roads, and the measured spectra of vegetation covered saline soils are not identical.
在地图矢量化方面，以在实际中最常使用的地形图为对象，主要研究了彩色扫描地形图中等高线和街区式居民地的自动提取。(1)提出了一种基于颜色键集合(color key set)技术的彩色地图分色改进算法，抑制了扫描图像中的颜色失真。(2)提出了一种了适合一般质量地形图中等高线自动提取的新方法，利用灰度线段分割修补等高线彩色分割结果和局部窗口分割技术，解决了等高线的断裂和粘连问题。(3)提出了先用Gabor滤波器检测晕线再提取居民地轮廓的方法，能够识别彩色地形图中街区式居民地。(4)研制了一个地形图矢量化软件——AutoVector，并已得到初步应用。
在遥感图像智能处理方面，主要研究了高分辨率全色遥感图像和多光谱遥感图像中纹理特征提取，以及目标检测与分类。纹理特征提取研究主要包括：(1)提出了一种在高分辨率全色图像上结合Gabor小波和ICA的纹理特征提取(ICAG)方法，获得了ICAGⅠ和ICAGⅡ两种纹理特征，用于表征纹理在不同尺度和方向上的高阶统计特性。(2)提出了一个ICA多尺度纹理算子，它先利用多个波段数据建立高维矢量再通过ICA提取纹理特征用于多光谱纹理分析。目标检测与分类研究主要包括：(1)提出了一种融合基于ICAGⅡ纹理特征的区域分割和边缘检测方法，能够自动识别高分辨率全色遥感图像中城镇和乡村级居民地。(2)提出了一种组合地物的光谱特征、几何形状特征和ICA多尺度纹理算子的分层分类方法，实现了多光谱图像中盐渍土的自动分类，解决了盐渍土与农田等非盐渍土地物边界不易区分，裸露盐渍土同居民地、道路之间的光谱混淆，以及有植被覆盖盐渍土光谱特征不一致等问题。
Nowadays scanned map vectorization and intelligent processing of remote sensing images is an active area attended widely in the fields of science research and application. They play a very important role for the creation and application of digital geographic information. This thesis focuses on the automatic extraction, recognition and classification of the main objects in the scanned topographic maps and remote sensing images.
In the scanned map vectorization, the thesis mainly studies the automatic extraction of the contour lines and residential area symbols in the chromatic scanned topographic maps. (1) A color key set technique based color separation modified algorithm of chromatic maps is developed, which can restrain color distortion in the scanned maps. (2) A novel method for extracting contour lines from common-conditioned topographic maps is presented, which solves contour line disconnection and conglutination by both contour line color segmentation results repaired with the line gray segmentation and local window segmentation. (3) A method to recognize the residential area symbols in the chromatic scanned topographic maps is offered, which firstly detects hatched lines by the Gabor filter and then extracts the contours of residential area symbols. (4) The topographic map vectorization software—AutoVector is developed and has been used initially.
In the intelligent processing of remote sensing images, the thesis mainly studies texture feature extraction, object detection and classification in both high resolution panchromatic and multispectral images. The research of texture feature extraction contains: (1) a method called ICAG is proposed by combining Gabor wavelets and independent component analysis (ICA) for extracting texture features in high resolution panchromatic images. This method constructs two texture features: ICAG I and ICAG II, which can be used to characterize the higher-order statistical properties of the texture in different scales and orientations. (2) An ICA based multiscale texture operator is presented, which firstly makes use of multiple bands data to construct the vectors with high dimensionality and then extracts features by ICA from these vectors for multispectral texture analysis. The research of object detection and classification contains: (1) a method for recognizing towns and villages in high resolution panchromatic images is presented by fusing area segmentation based on the ICAG II texture features and edge detection. (2) A layered classification method for saline soils classification in multispectral images is proposed by combining the spectral feature, the geometric feature and the ICA based multiscale texture operator. This method solves the problems, such as the edges among saline soils and other non-saline soils are difficult to be distinguished, bare vegetation saline soils have similar spectra to that of populated areas and roads, and the measured spectra of vegetation covered saline soils are not identical.
引文
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