共查询到20条相似文献,搜索用时 187 毫秒
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实测端元光谱和多光谱图像之间的模拟与细分 总被引:1,自引:0,他引:1
地物光谱特性是遥感应用的基础。本文以渭干河-库车河三角洲绿洲为研究区,首先选取裸土、植被两类地物作为研究对象,通过TM传感器的光谱响应函数,实现了将野外实测端元光谱拟合为多光谱离散光谱。其次在对TM图像的光谱波段进行细分的基础上,利用光谱知识库的数据支持来模拟获取具有更高光谱分辨率的细分光谱光学遥感图像,深入开展两种尺度相互转换的研究。结果表明:一、拟和的多光谱与TM像元光谱具有很好的相关性,在此基础上,采用线性算法建立端元光谱与遥感图像像元光谱的转换模型,实现了从实测端元光谱尺度向遥感多光谱像元尺度的定量光谱转换,为遥感定量分析奠定了一定基础。二、细分光谱模拟图像的方法能够较为可靠的模拟出真实高光谱分辨率图像的信息,模拟方法可信,达到了推广和验证的效果。 相似文献
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小波变换遥感图像的数据融合 总被引:3,自引:0,他引:3
利用小波变换方法进行多卫星遥感图像数据融合,分析不同长度的小波基对融合图像的影响,从信息的保持性、视觉效果及运用灵活性等方面与IHS、PCA融合算法进行了比较,从而探讨这一新算法在遥感图像分析应用中的可行性。 相似文献
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小波双三次插值搜索算法提高遥感图像分辨力 总被引:2,自引:1,他引:2
通过小波双三次插值中高频外推阈值门限选取与峰值信噪比变化关系的分析,提出了小波双三次插值搜索算法。该算法能够自动搜索到高频外推的最佳阈值门限,在不破坏光学遥感图像原始信息的情况下,提高图像的空间分辨力和峰值信噪比,有利于对图像的细节信息进行观察分析。实验表明,该算法的重建图像的峰值信噪比比全小波插值图像和小波双线性插值图像的峰值信噪比分别高6.5dB和2.4dB,熵提高到原图像的1.3倍,是一种提高光学遥感图像分辨力的有效算法。 相似文献
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针对多时相遥感影像变化检测问题,提出了一种多尺度和聚类分析的变化检测方法。该方法在差异影像的基础上,利用均值平移算法对差值法构造的差异影像进行平滑,结合平稳小波变换对平滑后的差异图像做两层的小波分解,由此构造由平滑后的差异图像以及提取的小波系数组成的特征向量,用 K 均值聚类对特征向量分类,通过区域生长将各类合并得到变... 相似文献
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基于边缘信息的偏振图像融合算法及评价 总被引:1,自引:1,他引:0
偏振遥感图像通常都采用强度、偏振度、偏振角来表征目标偏振特性.本文提出的基于边缘信息的偏振图像融合算法是将三幅偏振图像利用离散小波变换把图像分解成不同尺度的低频和高频部分,采用小波区域窗口和子区域窗口统计把小波系数分类成边缘和非边缘系数,通过这些方法进行有效的边缘细节信息提取.在融合处理中,低频图像的小波系数平均值作为融合后的低频系数,高频细节系数根据不同区域特征选择方法以及对应输入图像小波系数的窗口区域方差来确定融合后高频小波系数.仿真实验结果表明,这样使得融合后的图像细节更真实更丰富,图像的偏振特性体现更为充分,同时减少对源图像的预处理要求,使图像在整体上有较好的视觉效果.从而证明这种方法能够在保留图像微小细节方面获得满意的结果,且算法有效性优于其他的图像融合方法. 相似文献
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随着遥感技术的发展,遥感数据已应用到很多领域。从遥感影像中分析出地物空间特征和属性特征是遥感影像解译的关键。遥感图像分类是将图像中每个像元根据其在不同波段的光谱亮度、空间结构特征或其他相关信息,按照一定的规则或算法划分为不同的类别。利用非监督分类法尝试对ETM+遥感影像进行分析解译,提取水体专题信息,从结果来看专题信息提取效果较好。 相似文献
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We present a superresolution image reconstruction from a sequence of aliased imagery. The subpixel shifts (displacement) among the images are unknown due to the uncontrolled natural jitter of the imager. A correlation method is utilized to estimate subpixel shifts between each low-resolution aliased image with respect to a reference image. An error-energy reduction algorithm is derived to reconstruct the high-resolution alias-free output image. The main feature of this proposed error-energy reduction algorithm is that we treat the spatial samples from low-resolution images that possess unknown and irregular (uncontrolled) subpixel shifts as a set of constraints to populate an oversampled (sampled above the desired output bandwidth) processing array. The estimated subpixel locations of these samples and their values constitute a spatial domain constraint. Furthermore, the bandwidth of the alias-free image (or the sensor imposed bandwidth) is the criterion used as a spatial frequency domain constraint on the oversampled processing array. The results of testing the proposed algorithm on the simulated low- resolution forward-looking infrared (FLIR) images, real-world FLIR images, and visible images are provided. A comparison of the proposed algorithm with a standard interpolation algorithm for processing the simulated low-resolution FLIR images is also provided. 相似文献
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Xiangchun Liu Jing Yu Wei Song Xinping Zhang Lizhi Zhao Antai Wang 《计算机、材料和连续体(英文)》2020,65(2):1385-1395
With the development of satellite technology, the satellite imagery of the
earth’s surface and the whole surface makes it possible to survey surface resources and
master the dynamic changes of the earth with high efficiency and low consumption. As
an important tool for satellite remote sensing image processing, remote sensing image
classification has become a hot topic. According to the natural texture characteristics of
remote sensing images, this paper combines different texture features with the Extreme Learning Machine, and proposes a new remote sensing image classification algorithm.
The experimental tests are carried out through the standard test dataset SAT-4 and SAT-6.
Our results show that the proposed method is a simpler and more efficient remote sensing
image classification algorithm. It also achieves 99.434% recognition accuracy on SAT-4,
which is 1.5% higher than the 97.95% accuracy achieved by DeepSat. At the same time,
the recognition accuracy of SAT-6 reaches 99.5728%, which is 5.6% higher than
DeepSat’s 93.9%. 相似文献
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一种基于小波子带熵的遥感图像压缩算法 总被引:2,自引:0,他引:2
提出了一种使用小波子带熵进行比特分配的遥感图像压缩算法.对遥感图像进行小波提升分解后,分析了各高频子带能量百分比及其熵的变化趋势,在此基础上提出了一种新的快速比特分配方法-使用子带熵进行比特分配.然后对各个高频子带进行均匀量化,量化后的数据采用比特平面编码.对最高比特平面只记录该比特平面中非零系数的坐标,其它比特平面采用行程编码和Huffman编码方法进行压缩.实验结果表明,纹理复杂以及相对平坦的遥感图像使用该算法压缩后都可以获得很好的重构图像质量,峰值信噪比均大于34dB,而压缩比则与图像的复杂程度有关. 相似文献
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At an airport, the information of the number and positions of airplanes is very important for the applications of air navigation. Especially, the information from airplane extraction and identification is significant in both civil and military remote sensing. In this paper, according to the characteristics of airplanes and airport in satellite remote sensing images, a new airplane image segmentation algorithm is proposed based on improved pulse-coupled neural network (PCNN) with wavelet transform, and airplane identification algorithm is carried out by using modified Zernike moments. Firstly, for an original image, a PCNN model is improved and then used to do image segmentation by combining the wavelet transform. Then, in order to reduce the number of irrespective targets in the image and increase the processing speed, the airplanes in the original image are roughly detected on the characteristics of the segmented object contour geometries. Finally, the Zernike moments are modified and then applied to identify the roughly detected airplanes accurately. By comparing to the five traditional image segmentation algorithms for the same airplane images, the testing results show that the improved PCNN image segmentation algorithm can segment and detect airplane regions at an airport accurately at a high recognising rate and with high recognising stability, and it is not affected by the image shadows and rotations. 相似文献
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Abstract: A linear digital image correlation algorithm is proposed to eliminate noise‐induced bias in one‐dimensional translation estimation using noisy images. The algorithm uses linear interpolation for both initial and current images at off‐pixel positions and solves directly the displacement parameter by minimizing a sum‐of‐squared‐differences coefficient. Both analytical results and numerical simulations using synthetic image sets show that there is indeed no noise‐induced bias in the displacement estimation using the proposed algorithm if the off‐pixel positions in both images are chosen properly according to the relative displacement between two images. When the displacement is only known initially within a range of ±0.5 pixels from the actual displacement, an iterative procedure using the algorithm is able to obtain the displacement estimation with a residual bias that converges to the noiseless subpixel approximation bias. A further refinement of the off‐pixel analysis algorithm will be needed so the remaining residual bias due to subpixel approximation can also be significantly reduced. 相似文献
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无人机航空遥感电子稳像系统中,稳像的关键技术之一是影像特征点的选取,其中图像角点是遥感影像中重要的特征信息,准确地选取角点可提高图像处理的精度。然而现有的图像角点检测算法多因计算速度慢不能满足视频图像数字稳像的实时性。因此提出了一种基TSUSAN角点检测算法的改进算法。新算法分析了影像中角点所在区域的灰度变化特征,改进了SUSAN角点检测算法中的判断准则,提高了算法的精度和速度。实验结果表明,改进的算法可较大幅度的提高运算速度,满足稳像技术对视频图像实时处理的要求。 相似文献
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本文提出了一种多重约束下由粗到精的多源图像自适应子像素级配准算法.该算法采用影像特征点作为匹配基元,利用具有不同精度等级的组合判据法、整体松弛法、最小二乘法实现由粗到精的匹配,同时在匹配过程中加入了多重约束,如定位点控制约束、交叉匹配约束、连续控制约束,以保证获取的配准控制点的可靠性和剔除粗差点.此外,该算法利用配准控制点自适应地构建整个图像的三角网,最后依据改进的三角形填充算法对目标图像进行逐像点纠正.对同源和非同源的遥感图像的实验证明,SPOT4全色图像(10m/pixel)和SPOT5多光谱图像(10m/pixel)的配准精度分别达到6~7m和5~6m. 相似文献
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基于虚拟点的可见光和SAR图像配准研究 总被引:1,自引:1,他引:0
本文以机场场景下的可见光和SAR图像为研究对象,提出了一种基于虚拟点特征的可见光和SAR图像配准方法.该方法以虚拟点特征和控制点匹配技术为基础,处理具有全局仿射几何失真的异源图像配准问题.首先根据两类图像的特点,使用Canny算子和一种兴趣算子提取两幅图像中的共有特征一直线特征,然后在直线特征的基础上拟合虚拟点特征,采用基于特征一致的粗配准和基于虚拟点特征的精确配准相结合的方法,对两幅图像实现由粗到精的自动配准,实验结果表明,本文方法可行且能取得较高的配准精度. 相似文献