共查询到20条相似文献，搜索用时 31 毫秒
1.
Normally, to detect surface water changes, water features are extracted individually using multi-temporal satellite data, and then analyzed and compared to detect their changes. This study introduced a new approach for surface water change detection, which is based on integration of pixel level image fusion and image classification techniques. The proposed approach has the advantages of producing a pansharpened multispectral image, simultaneously highlighting the changed areas, as well as providing a high accuracy result. In doing so, various fusion techniques including Modified IHS, High Pass Filter, Gram Schmidt, and Wavelet-PC were investigated to merge the multi-temporal Landsat ETM+ 2000 and TM 2010 images to highlight the changes. The suitability of the resulting fused images for change detection was evaluated using edge detection, visual interpretation, and quantitative analysis methods. Subsequently, artificial neural network (ANN), support vector machine (SVM), and maximum likelihood (ML) classification techniques were applied to extract and map the highlighted changes. Furthermore, the applicability of the proposed approach for surface water change detection was evaluated in comparison with some common change detection methods including image differencing, principal components analysis, and post classification comparison. The results indicate that Lake Urmia lost about one third of its surface area in the period 2000–2010. The results illustrate the effectiveness of the proposed approach, especially Gram Schmidt-ANN and Gram Schmidt-SVM for surface water change detection. 相似文献
2.
利用SAR影像配准偏移量提取地表形变的方法与误差分析 总被引：1，自引：1，他引：0
单一的InSAR观测技术可提取地表沿雷达视线方向(LOS)上的一维位移,而利用SAR影像配准过程中的同名像素偏移量可提取地表沿雷达方位向(近南北向)与距离向(近东西向)的二维形变场,与LOS方向的一维形变形成优势互补。本文在分析SAR影像配准偏移量提取地表形变场方法的基础上,推导建立了雷达方位向与距离向形变提取的误差模型,探讨了该方法提取地表形变的主要误差源。以Bam地震ASAR影像和玉树地震PALSAR影像为数据源,分别开展同震形变场的提取与误差分析试验,结果表明,基于SAR像素配准偏移量提取同震形变场的精度主要受匹配窗口尺寸与过采样因子影响,形变提取误差随匹配计算窗口的增大而减小,形变提取精度随过采样因子的增大有适量提高,地形起伏效应在高差较大的SAR影像区域中表现较为显著。 相似文献
3.
为了改变传统的变形监测方法存在的费工、费时与危险等弊端,将数字图像处理技术应用于变形监测是一种行之有效的方法。通过对南京明城墙裂缝变形监测图像进行创新的像素标定以及灰度转换等一系列巧妙的图像处理后,获得了裂缝的变形值。实验结果表明,基于数字图像处理技术的变形监测方法,不仅具有较高的精度和可操作性,而且与传统测量方法相比能够显著提高工作效率,对裂缝的定量化变形监测实现非接触式无损测量的目标具有重要的意义。 相似文献
4.
立体影像匹配是自动提取SPOT影像高程信息的关键技术。本文根据SPOT影像在几何构像关系和影像质量上的特点,提出了多级匹配的结构策略。实际像对匹配实验表明,多级匹配法具有较好的可靠性和精度水平,而且运算速度快,在快速生成DEM数据辅助遥感信息分析方面,有重要的应用价值。 相似文献
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基于3m分辨率的TerraSAR-X数据对覆盖西安地区的活动地裂缝进行了定位与监测研究。数据为2009-12-03～2010-03-23共6景Strip模式数据。实验结果显示,高分辨率TerraSAR数据是监测地裂缝很好的数据源,但为了获取高精度的监测成果还需要特别考虑时间和基线去相干因素。二轨法监测结果显示,活动地裂缝往往出现在稳定区域与形变区域的转折部位,而采用人工角反射器技术可以监测出mm量级的地裂缝相对形变信息。 相似文献
6.
由于噪声的干扰,常规的图像边缘检测方法往往效果不佳,因此提出了一种基于改进BP网络的边缘检测方法。在充分考虑边缘和噪声本质区别的基础上,构造具有较强抗噪能力的特征向量,然后用样本图像对四层BP网络采用改进BP算法进行训练。最后,将训练后的网络用于图像的边缘检测。实验证明这种方法是有效的。 相似文献
7.
基于边缘提取和改进型整体松弛匹配算法的InSAR复图像配准方法 总被引：1，自引：1，他引：0
配准精度是InSAR合成孔径雷达干涉成像技术中的重要指标。为获得高精确度的测量结果,提出一种包括概略配准、像素级初配准和亚像素级精配准三个环节的逐级提高精度的InSAR复图像配准方法。利用EnView软件提供的经度和纬度实现概略配准、采用基于多边形结构和边缘提取的像素级初匹配方法大大提高匹配速度。考虑以往的匹配算法都是基于能量图进行并且忽略了整体性,采用基于整体松弛匹配和相位最小二乘匹配相结合的亚像素级精匹配算法减少误匹配率,提高匹配精度。实验结果证明该方法具有良好的性能。 相似文献
8.
人们总是期望用较高分辨率的遥感影像来检验或评价相对低分辨率的遥感影像的分类结果的正确性，比如用航空影像检验ＴＭ的分类结果，用ＴＭ影像检验ＮＯＡＡ的分类结果。然而进行检验的首要关键的问题是将两幅不同分辨率的遥感影像在空间准确配准。事实证明，在空间域进行强制叠合是不成功的，因为二者没有可比的共同基准。两物相比必须要有一个共同的基础，作者认为遥感影像的空间频谱是一个较好的可以相互比较的基础，人们可以设法使空间尺度不同的两幅遥感影像在空间频谱上具有一致性，也就是说对相对高分辨率的影像进行适当的低通滤波而粗化，并通过它与相对的低分辨率的遥感影像进行错动，求取相关系数值，当相关系数达到最大值时可被认为是最佳的配准状况。本文以１：１００００的黑白航空像片为准，对应用ＴＭ影像估算冬小麦播种面积的精度进行了对比检验。结果表明，在传统的监督分类，Ｋ－Ｔ变换或混合像元分解方法中，混合像元分解方法的精度最高。 相似文献
9.
顾及灰度和梯度信息的多模态影像配准算法 总被引：1，自引：1，他引：0
基于特征匹配的多模态影像配准方法无法达到像素级配准精度要求。本文研究了一种顾及灰度和梯度信息的多模态影像配准算法。基于马尔科夫随机场（MRF）的非参数化配准模型充分利用多模态影像的图像信息进行相似性测量,同时考虑了灰度及梯度统计信息,求解方法上对值空间进行离散化,提高收敛速度。通过3组多模态影像的配准试验,验证了该算法的可行性。试验表明：本文算法的配准效果优于基于人工刺点的多项式模型配准和只考虑灰度信息的多模态影像配准;与此同时,该算法对于较大形变的影像配准也具有一定的适用性。在空间精度方面,平均配准误差小于1个像素,最大配准误差小于2个像素。 相似文献
10.
《International Journal of Digital Earth》2013,6(1):72-82
Abstract Digital elevation model (DEM) matching techniques have been extended to DEM deformation detection by substituting a robust estimator for the least squares estimator, in which terrain changes are treated as gross errors. However, all existing methods only emphasise their deformation detecting ability, and neglect another important aspect: only when the gross error can be detected and located, can this system be useful. This paper employs the gross error judgement matrix as a tool to make an in-depth analysis of this problem. The theoretical analyses and experimental results show that observations in the DEM matching algorithm in real applications have the ability to detect and locate gross errors. Therefore, treating the terrain changes as gross errors is theoretically feasible, allowing real DEM deformations to be detected by employing a surface matching technique. 相似文献
11.
针对常规SAR影像匹配方法在地形起伏较大区域无法获取理想的SAR立体影像匹配结果的问题,该文提出了一种基于模拟纠正影像的SAR立体影像匹配方法。利用观测区域粗分辨率DEM进行SAR影像模拟,进而获取几何纠正SAR影像,在几何纠正SAR影像上实现影像匹配,等效于常规基于灰度影像匹配中进行的影像粗配准工作,并且相比于常规粗配准,该等效粗配准过程能够均衡地顾及到整幅影像的像元,最终实现了地形起伏较大区域的高精度SAR立体影像匹配。采用COSMO-Skyped影像数据进行了实验,实验结果表明,匹配精度达到了3个像素左右,比常规的基于灰度影像匹配方法有较大提高,能够有效解决地形起伏较大区域SAR立体影像匹配问题。 相似文献
12.
柴新宇 《测绘与空间地理信息》2017,(1)
以地图测绘、空间信息遥感、摄影测量学为背景的,根据多视影像匹配的理念和方法,按单点最小二乘匹配扩展为基于地面元的多点(以三片为例)的最小二乘匹配,基于改进的VLL讨论了一种基于多视影像的最小二乘影像匹配的方法,高精度的像素影像可以由这种特有的方法进行处理分析,像素的精度可达千分之一。进行相关分析后表明:进行高精度数字影像匹配融合时选择恰当影像匹配模型的匹配策略或由差异的匹配策略结合使用可更好地提高匹配的成功率和可适应性,从而降低误匹配或者漏匹配的同名点。 相似文献
13.
本文提出将矢量空间数据与影像数据间配准转换到矢量空间数据间匹配的思路,并开展了相关研究。本文主要思路是通过对影像数据进行基于形状特征的提取及矢量化,然后利用矢量空间数据间匹配方法对矢量化后数据和现有矢量空间数据进行匹配,获取匹配实体对;在获取的匹配实体对中选取控制点对,在矢量化后数据中选取控制点,将所选取的控制点反馈到原始遥感影像上进而获得控制点相应的像元坐标;最后应用矢量化后数据中控制点的像元坐标数据和现有矢量空间数据中对应的同名点坐标数据对原始影像进行几何纠正,从而实现矢量空间数据和影像数据的配准。 相似文献
14.
15.
提出一种基于向量场模型的多光谱图像多尺度边缘检测算法,并在算法中引入两种梯度方向量化邻域模型。首先,对多光谱图像进行二进小波变换,得到每个波段图像在不同尺度上的细节系数,然后根据向量场模型计算多光谱图像的梯度幅值和梯度方向,选择适宜的邻域模型对梯度方向进行量化,最后沿量化后的方向获取由细到粗的多层次边缘信息。对QuickBird多光谱图像上农田、厂房等地物进行多尺度边缘提取,定性分析了图像分辨率大小与地物尺寸关系在不同尺度边缘信息的表征;利用F测度,定量评价了检测结果的边缘准确度。与传统算子检测结果对比表明,利用向量场模型综合了所有波段的边缘信息,减少了多波段图像边缘信息的不一致性,引入的量化邻域模型能够有效地获取完整的多尺度边缘点。 相似文献
16.
A. Senthil Kumar V. Keerthi A.S. Manjunath Harald van der Werff Freek van der Meer 《International Journal of Applied Earth Observation and Geoinformation》2010
Classification of hyperspectral images has been receiving considerable attention with many new applications reported from commercial and military sectors. Hyperspectral images are composed of a large number of spectral channels, and have the potential to deliver a great deal of information about a remotely sensed scene. However, in addition to high dimensionality, hyperspectral image classification is compounded with a coarse ground pixel size of the sensor for want of adequate sensor signal to noise ratio within a fine spectral passband. This makes multiple ground features jointly occupying a single pixel. Spectral mixture analysis typically begins with pixel classification with spectral matching techniques, followed by the use of spectral unmixing algorithms for estimating endmembers abundance values in the pixel. The spectral matching techniques are analogous to supervised pattern recognition approaches, and try to estimate some similarity between spectral signatures of the pixel and reference target. In this paper, we propose a spectral matching approach by combining two schemes—variable interval spectral average (VISA) method and spectral curve matching (SCM) method. The VISA method helps to detect transient spectral features at different scales of spectral windows, while the SCM method finds a match between these features of the pixel and one of library spectra by least square fitting. Here we also compare the performance of the combined algorithm with other spectral matching techniques using a simulated and the AVIRIS hyperspectral data sets. Our results indicate that the proposed combination technique exhibits a stronger performance over the other methods in the classification of both the pure and mixed class pixels simultaneously. 相似文献
17.
This study presents an approach for the automatic extraction of dynamic sub-boundaries within existing agricultural fields from remote sensing imagery using perceptual grouping. We define sub-boundaries as boundaries, where a change in crop type takes a place within the fixed geometry of an agricultural field. To perform field-based processing and analysis operations, the field boundary data and satellite imagery are integrated. The edge pixels are detected using the Canny edge detector. The edge pixels are then analyzed to find the connected edge chains and from these chains the line segments are detected using the graph-based vectorization method. The spurious line segments are eliminated through a line simplification process. The perceptual grouping of the line segments is employed for detecting sub-boundaries and constructing sub-fields within the fixed geometry of agricultural fields. Our strategy for perceptual grouping involves the Gestalt laws of proximity, continuation, symmetry and closure. The processing and analysis operations are carried out on field-by-field basis. For each field, the geometries of sub-boundaries are determined through analyzing the line segments that fall within the field and the extracted sub-boundaries are integrated with the fixed geometry of the field.The experimental validation of the approach was carried out on the SPOT4 multispectral (XS) and SPOT5 XS images that cover an agricultural area located in the north-west section of Turkey. The overall matching percentages between the reference data and the automatically extracted sub-boundaries were computed to be 82.6% and 76.2% for the SPOT5 and SPOT4 images respectively. The higher matching percentage of the SPOT5 image is due to the fact that some of the boundaries present in the SPOT5 image were not detected in the coarser resolution SPOT4 image. For the SPOT5 image, of the total 292 fields processed, 177 showed a total agreement between the detected segments and the reference data. For the SPOT4 image, 154 fields showed a total agreement between the detected segments and the reference data. 相似文献
18.
SAR影像与光学影像的高斯伽玛型边缘强度特征匹配法 总被引：1，自引：1，他引：0
提出了一种基于影像边缘强度图描述的SAR影像与光学影像匹配方法。首先对影像进行粗纠正,消除影像之间的尺度和旋转变化;其次,改进相位一致性特征检测方法,提取对影像相干斑噪声稳健的特征点;然后基于高斯伽玛型双边窗口比值算子计算影像边缘强度图,在此基础上构造不变特征描述符;最后联合几何约束条件,实现SAR影像与光学影像匹配。试验结果证明,与现有方法相比,本文方法能够大幅提高SAR影像与光学影像匹配结果中的正确匹配特征数量以及影像配准精度。 相似文献
19.
Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods. 相似文献