共查询到19条相似文献，搜索用时 125 毫秒
1.
2.
为了精准地从高分遥感影像提取植被信息,需要消除遥感影像阴影。本文提出一种高分遥感影像波段最优组合阴影检测与基于颜色恒常的阴影消除技术,从而避免了阴影对提取植被信息的影响。采用覆盖城区QuickBird影像进行试验,结果表明,本文方法既能检测阴影,也能消除高分遥感影像阴影,是一种实用的遥感影像阴影处理方法。 相似文献
3.
包络线去除的丘陵地区遥感影像阴影信息重建 总被引：1，自引：0，他引：1
中国西南丘陵常态山和喀斯特山交错分布,遥感影像普遍存在山体阴影,分布零散且无规律,基于DEM的地形校正模型(C校正等)虽然算法成熟、易于操作,但在复杂地形区存在误差。引入基于相似像元包络线的阴影校正方法(CR校正),按照阴影提取、包络线去除、相似像元寻找和阴影亮度重建的步骤,采用西南丘陵地区Landsat 8 OLI影像进行验证实验。结果表明:CR校正后,阴影区的视觉特征与邻近非阴影区趋于一致,阴影像元亮度有明显提升;校正后影像主要波段标准差减小,与非阴影区参考光谱的相对均方根误差在2.919%以内,最低仅为0.516%;自动分类精度从43.59%提高到61.57%,CR校正有效提高了有阴影的丘陵地区遥感影像质量。 相似文献
4.
5.
多光谱影像NDVI阴影影响去除模型 总被引：1，自引：0，他引：1
归一化植被指数(NDVI)在植被多光谱遥感反演中占据尤为重要的地位,而遥感影像中普遍存在的阴影对NDVI的精度产生很大的影响,因此去除阴影对植被NDVI的影响对更精确的定量化研究具有应用价值。本文基于光照区和阴影区的太阳辐射能量差异,模拟出同一植被在光照区和阴影区的辐亮度,分析阴影对NDVI的影响机理;利用植被固有反射率谱间关系,引入对阴影极敏感的且与植被信息相关性小的归一化暗像元指数NDPI(Normalized Dark Pixel Index),分析同一植被处于光照区与阴影区的NDVI关系,构建以光照区植被NDVI为基准的NDVI阴影影响去除模型NSEE (NDVI Shadow-Effect-Eliminating),并应用于Landsat 8 OLI影像进行验证。结果表明:NDVI阴影影响基本去除,阴影区NDVI接近正常值,且光照区NDVI保持稳定;有效解决了阴影导致NDVI统计直方图的偏态问题,使其更接近正态分布;与验证影像NDVI沿剖面线逐像元比对发现,植被NDVI阴影影响基本去除;均方根误差RMSE为0.067。本模型能够将本身NDVI值很低的像元与阴影导致NDVI降低的植被像元区分开,符合实际地物情况;模型基于影像自身信息,去除NDVI阴影影响的同时,有效保持了NDVI的相对空间关系;本文基于物理机理构建模型,模型表达简洁、易于应用,且仅依赖于影像自身信息,无需异源数据,计算方便且高效。 相似文献
6.
针对水体、偏蓝色地物会影响高分影像阴影检测精度,本文提出了一种适用于GF-1影像的城市高大地物阴影检测方法。首先,在统计分析GF-1影像中阴影、水体及深色地物等典型地物光谱特征的基础上,利用主成分变换方法分割阴影与非阴影区域,分离后的阴影区域含有水体、深色地物信息;其次,对HSV色彩空间的V分量利用阈值法分割阴影和非阴影区域,分离后结果含有暗色植被,但不含有水体跟深色地物信息。最后,对两次计算结果进行逻辑与运算,从而剔除混合阴影区域中水体、深色地物以及暗色植被等信息,获得高精度阴影区信息。实验表明,该方法具有较好的普适性和可操作性,既能够削弱水体、偏蓝色地的影响,又能够高效、准确地提取出GF-1影像中的阴影信息。 相似文献
7.
基于HSI色彩空间的资源三号影像阴影检测 总被引：1，自引：0，他引：1
由于遥感影像上某些区域的光照辐射不足,不可避免地会产生阴影,阴影意味着图像信息的损失,而遥感影像的阴影检测在地物的识别和影像匹配方面具有重要意义。本文主要介绍的是基于HIS色彩空间的阴影检测方法,在检测过程中,根据阴影高色调低亮度的特性,结合大津法计算比值图像最佳阈值进行遥感影像阴影检测,并且在RGB色彩空间计算G分量的最佳阈值来排除树木植被和一些非阴影区域对阴影检测的影响。同时采用国产高分辨遥感卫星——资源三号的同一地区不同季节和不同太阳高度角的遥感数据进行阴影的对比检测。实验结果表明:本文基于HIS色彩空间的阴影检测方法可以快速有效地检测出影像上的阴影,并且能区分树木、河流等暗色物体。 相似文献
8.
《地理空间信息》2017,(8)
针对高分影像阴影检测精度易受水体、偏蓝色地物影响的问题,结合GF-1影像自身特点,提出一种集主成分变换、图像特征计算、逻辑非运算和形态学闭运算于一体的阴影检测方法。对GF-1影像多光谱数据、全色数据进行正射校正和信息融合,可实现光谱与分辨率信息的最大化利用,并最大程度地突出阴影信息,增大阴影与其他地物的差异。其次,建立基于主成分变换的阴影检测方法 PC1/NIR和图像特征计算Rg_nir,得到初始阴影信息和水体信息;用初始阴影信息与水体信息作逻辑非运算,剔除水体,并利用形态学闭运算使得阴影区域更加连续、饱满。实验表明,该方法既能准确地检测出GF-1影像中的阴影信息,又能有效削弱水体、偏蓝色等地物的影响。 相似文献
9.
建筑物高度信息对城市景观规划设计、城市人居和生态环境评估等都具有重要作用。针对当前卫星遥感影像提取建筑物高度研究中存在精度较低、人工干预程度过多的问题,本文基于GF-2卫星遥感影像数据,综合建筑物阴影指数(EMSI)、归一化植被指数(NDVI)和地表反射率等3个参数,实现了建筑物阴影的自动化提取,进而依据空间几何学关系,实现了建筑物高度的快速估算,最后对研究结果进行了实地检验。研究表明,利用建筑物阴影指数、NDVI、地表反射率等3个参数可有效提取建筑物阴影,且利用建筑物阴影进行建筑物高度估算的平均精度达到了95.40%,证明了高分二号卫星影像在提取建筑物高度方面具有较高的可行性。 相似文献
10.
Landsat TM数据不同辐射校正方法对土地覆盖遥感分类的影响 总被引：2，自引：0，他引：2
本文主要是探索Landsat TM数据不同辐射校正方法对土地覆盖遥感分类的影响。介绍了使用的3种不同辐射校正方法(ATCOR3、FLAASH以及查找表)和两种分类算法。在分类实验部分,根据样本的地理坐标在3景校正影像中分别采集训练样本并训练各自的分类器,并交叉用于其他辐射校正影像的土地覆盖遥感分类。实验结果表明:(1)用于分类器训练的样本采集自待分类影像时的分类精度明显高于采集自其他影像的分类精度;(2)3种辐射校正影像的分类结果存在差异,其中使用ATCOR3和FLAASH方法校正后影像的分类结果有更相近的精度;(3)辐射校正对分类类别的影响不同,其中对森林类型影响最大,对裸地等其他类别影响相对较小。 相似文献
11.
Shadows commonly exist in high resolution satellite imagery, particularly in urban areas, which is a combined effect of low sun elevation, off-nadir viewing angle, and high-rise buildings. The presence of shadows can negatively affect image processing, including land cover classification, mapping, and object recognition due to the reduction or even total loss of spectral information in shadows. The compensation of spectral information in shadows is thus one of the most important preprocessing steps for the interpretation and exploitation of high resolution satellite imagery in urban areas. In this study, we propose a new approach for global shadow compensation through the utilization of fully constrained linear spectral unmixing. The basic assumption of the proposed method is that the construction of the spectral scatter plot in shadows is analogues to that in non-shadow areas within a two-dimension spectral mixing space. In order to ensure the continuity of land covers, a smooth operator is further used to refine the restored shadow pixels on the edge of non-shadow and shadow areas. The proposed method is validated using the WorldView-2 multispectral imagery collected from downtown Toronto, Ontario, Canada. In comparison with the existing linear-correlation correction method, the proposed method produced the compensated shadows with higher quality. 相似文献
12.
This study addresses the problem of shadows in multi-temporal imagery, which is a key issue with change detection approaches based on image comparison. We apply image-to-image radiometric normalizations including histogram matching (HM), mean-variance (MV) equalization, linear regression based on pseudo-invariant features (PIF-LR), and radiometric control sets (RCS) representing high- and low-reflectance extrema, for the novel purpose of normalizing brightness of transient shadows in high spatial resolution, bi-temporal, aerial frame image sets. Efficient shadow normalization is integral to remote sensing procedures that support disaster response efforts in a near-real-time fashion, including repeat station image (RSI) capture, wireless data transfer, shadow detection (as precursor to shadow normalization), and change detection based on image differencing and visual interpretation. We apply the normalization techniques to imagery of suburban scenes containing shadowed materials of varied spectral reflectance characteristics, whereby intensity (average of red, green, and blue spectral band values) under fully illuminated conditions is known from counterpart reference images (time-1 versus time-2). We evaluate the normalization results using stratified random pixel samples within transient shadows, considering central tendency and variance of differences in intensity relative to the unnormalized images. Overall, MV equalization yielded superior results in our tests, reducing the radiometric effects of shadowing by more than 85 percent. The HM and PIF-LR approaches showed slightly lower performance than MV, while the RCS approach proved unreliable among scenes and among stratified intensity levels. We qualitatively evaluate a shadow normalization based on MV equalization, describing its utility and limitations when applied in change detection. Application of image-to-image radiometric normalization for brightening shadowed areas in multi-temporal imagery in this study proved efficient and effective to support change detection. 相似文献
13.
14.
利用云下阴影实现陆地上空气溶胶和地表反射率的同时反演—理论方法和模拟 总被引：3，自引：0，他引：3
卫星探测信号包含大气中分子和粒子的散射贡献以及地表反射的贡献,在陆地上空二者的贡献相当,并且陆地地表反射率在时间和空间上极度不均一,因此,很难区分二者的各自贡献从而定量提取大气气溶胶和地表反射率,陆地上空气溶胶的反演也一直是一个极具挑战性的课题.而高分辨率卫星资料如TM5的可见光通道能够很好地区分云和云下阴影,如果云是不透光的,在阴影上空,卫星信号仅包含大气散射贡献和地表漫反射贡献,而在邻近的非阴影区上空,卫星探测信号还包含地表直接反射的贡献,根据这个原理,利用辐射传输模式分析了阴影区和非阴影区上空卫星探测的辐射量差别与地表反射率和大气气溶胶的关系,提出一种利用云下阴影来同时提取阴影上空大气气溶胶和地表反射率的单波长反演方案,并对气溶胶单次散射反照率,散射相函数,测量精度以及地表反射率的不均一性进行了敏感性分析. 相似文献
15.
利用辐射传输机理对复杂山区进行地形辐射校正,可以全面地考虑太阳直接辐射亮度、天空散射辐射亮度及邻近地表反射辐射亮度3部分因素,从而取得较好的校正结果。遮蔽因子的准确提取是决定地形校正结果的关键因素。本文使用同一个辐射传输模型,针对同一片地表裸露山区的SPOT-5全色影像,分别使用对应的DEM和直方图阈值分割法计算遮蔽因子,并将得到的校正结果进行对比发现：在DEM精度不够高的情况下,使用直方图阈值分割法计算遮蔽因子,可以得到更好的地形校正效果,充分证明了直方图阈值分割法计算遮蔽因子的优势及使用价值。 相似文献
16.
针对高分辨率卫星影像,提出一种特征分量构建与面向对象结合的阴影提取方法。分析遥感阴影光谱特性,构建彩色不变特征C3、亮度特征I、主成分第一特征量PC1以及蓝色波段和近红外波段归一化比率特征RATIOb_nir,增强阴影信息。采用线性变换将几个特征分量Digital Number(DN)值归一化到相同范围,对这几个分量进行综合分析。以I和PC1分量为输入对影像进行多尺度分割,建立包括波段均值、标准差、最大差异等特征的规则集,实现面向对象的阴影信息提取。选取20幅QuickBird影像为例进行阴影提取实验,平均总体精度为97%,平均用户精度为96%,平均Kappa系数为0.94。实验结果表明,相对传统基于像素信息提取方法,本文方法提取阴影斑块完整,无破碎图斑;相对基于原始光谱的面向对象方法,本文方法提取精度更高。 相似文献
17.
建筑物高度是现代化都市监测、规划、管理及各城市经济活动中的基础性数据,为实现建筑物高度信息的提取,本文提出了一种基于玻尔兹曼曲线的建筑物高度反演方法。首先,利用建筑物影像的光谱特性,采用多尺度分割和遥感指数分类的办法获取建筑物阴影感兴趣区域,根据玻尔兹曼曲线函数拟合获取阴影的亚像素位置,线性拟合得到阴影边界;然后,根据太阳、卫星、建筑物和其阴影的几何关系,构建高度反演模型,估算建筑物高度;最后,选择宁海为研究区,选取在轨的主流亚米级高分二号、高景一号、北京二号、WorldView-2卫星遥感数据进行精度验证。试验结果表明,计算的建筑物高度中误差优于2.5 m,可用于一般的城市卫星遥感监测。 相似文献
18.
Multi-temporal aerial imagery captured via an approach called repeat station imaging (RSI) facilitates post-hazard assessment of damage to infrastructure. Spectral-radiometric (SR) variations caused by differences in shadowing may inhibit successful change detection based on image differencing. This study evaluates a novel approach to shadow classification based on bi-temporal imagery, which exploits SR change signatures associated with transient shadows. Changes in intensity (brightness from red–green–blue images) and intensity-normalized blue waveband values provide a basis for classifying transient shadows across a range of material types with unique reflectance properties, using thresholds that proved versatile for very different scenes. We derive classification thresholds for persistent shadows based on hue to intensity ratio (H/I) images, by exploiting statistics obtained from transient shadow areas. We assess shadow classification accuracy based on this procedure, and compare it to the more conventional approach of thresholding individual H/I images based on frequency distributions. Our efficient and semi-automated shadow classification procedure shows improved mean accuracy (93.3%) and versatility with different image sets over the conventional approach (84.7%). For proof-of-concept, we demonstrate that overlaying bi-temporal imagery also facilitates normalization of intensity values in transient shadow areas, as part of an integrated procedure to support near-real-time change detection. 相似文献
19.
Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing. 相似文献