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1.
一种基于小波包变换的遥感影像融合方法 总被引:12,自引:0,他引:12
针对多光谱遥感影像和全色遥感影像,提出了一种基于小波包变换的遥感影像融合方法。新方法首先对多光谱遥感影像进行PCA变换;其次对多光谱遥感影像的第一主分量和全色遥感影像进行小波包变换;然后保留多光谱影像第一主分量的低频近似分量,融合它们的高频细节分量;最后,做小波包反变换,得到新的多光谱遥感影像第一主分量,再做PCA反变换,得到新的多光谱遥感影像。与PCA变换融合方法、IHS变换融合方法和小波变换融合方法等方法在主观视觉效果分析和客观统计参数两方面做了比较,新方法是有效的,不仅较大地增强了结果影像的空间细节表现能力,而且很好地保留了多光谱影像的光谱信息。 相似文献
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对于多光谱和全色波段遥感影像融合而言,影像问光谱响应范围的差异是造成融合结果光谱畸变的重要原因。方法通过对遥感影像成像过程中的参数进行合理地近似,将多光谱影像有机地结合为光谱响应范围与全色波段接近的、低分辨率的“多光谱全色波段”。利用特定的小波融合法则,将全色波段中适量的空间信息融入到“多光谱全色波段”中,并根据构建“多光谱全色波段”时各多光谱影像所占的权重,将融入的空间信息逐像元地分解到各个多光谱波段,从而较好地削弱了融合影像间光谱响应范围的差异所造成的光谱畸变。通过对IKONOS遥感影像进行融合实验,验证了本文方法较传统方法具有更高的性能。 相似文献
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通过将较低空间分辨率的多光谱影像和较高空间分辨率的全色波段影像融合产生兼具多光谱和高空间分辨率特征影像是提高资源环境监测精度的重要途径之一。本文提出了一种计算简单、光谱保真性好的影像融合算法。该方法根据影像局域统计特征,建立融合方程,以表征全色影像空间结构和多光谱影像光谱信息的统计量为约束,求解融合系数,实现影像融合。试验结果表明该方法光谱保真性好、适应性强,具有一定的应用潜力。 相似文献
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为了提高SAR影像的解译水平,避免通常基于小波变换的融合方法造成的SAR影像信息损失,本文提出一种基于a’trous小波与广义HIS变换的SAR与多光谱影像融合方法,在将多光谱影像转换到HIS空间后,应用a’trous小波对I分量进行分解,通过加法的形式将多光谱影像的高频分量信息与SAR影像信息集成,并根据解译的需要,通过改变阈值来控制对多光谱影像信息的集成幅度。实验选取一组TM多光谱影像与ERS-2SAR影像进行融合研究,并将融合结果与另一小波融合方法融合结果进行视觉比较与统计分析。结果表明,另一小波融合方法的融合结果与本文方法融合结果阈值τ=1时的结果接近,而本文方法却可以根据不同的应用需要,在完整保留了SAR影像信息的基础上,通过调节多光谱影像信息的注入程度,为获取更能满足解译需要的SAR融合影像提供更多选择,拥有更好的鲁棒性。 相似文献
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众所周知,多光谱与雷达影像融合具有重要的意义,但雷达影像小尺度的纹理特征在先前的融合方法中却没有被考虑。为了更好地对多光谱与雷达影像进行融合,基于双正交小波变换,提出了一种小尺度纹理影像参与融合的三影像小波融合方法。该方法借鉴多通道滤波及基于亮度调节的平滑滤波(SFIM)融合的原理,首先提取多时相雷达影像的小尺度纹理数据;然后再将该纹理数据、单时相JERS-1SAR数据及TM多光谱数据进行小波融合。分析表明,该方法的融合结果较雷达与多光谱影像小波融合的结果不仅具有更丰富的光谱特征,而且由于继承了雷达影像丰富的小尺度纹理特征,因而具有更高的清晰度。实验证明,该方法可获得较好的融合结果,是一种切实有效的融合法。 相似文献
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基于亮度平滑滤波调节(SFIM)的SPOT5影像融合 总被引:3,自引:0,他引:3
遥感影像融合不仅要求提高原多光谱影像的空间分辨率,更重要的是保留影像的光谱信息,减少失真。为分析SFIM算法融合SPOT-5影像的光谱保真效果,首先采用IHS、小波和SFIM算法对SPOT-5的全色影像和多光谱影像进行融合,生成新的高分辨率多光谱影像。然后采用均值、相关系数、熵、标准差、梯度五个指标对SFIM不同滤波窗口的融合结果评价;最后采用以上定量评价指标对不同方法的融合结果进行分析评价。结果表明:和传统的IHS、小波融合方法相比,SFIM融合不仅提高了影像的空间分辨率和清晰度,而且较好地保持了原多光谱影像的光谱特征。 相似文献
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研究了基于ARSIS概念的遥感影像的小波包融合方法。利用小波包分解高分辨率影像和多光谱影像,在融合影像的低频小波包系数重构时采用波段间交互构建模式,即包含了多光谱影像低频小波包系数,也包含了高分辨率影像低频小波包系数。融合影像的高频小波包系数以局部方差为规则进行择优选取。融合实验结果证明,新方法在对原多光谱影像信息的保持上优于IHS方法,同时在保持高分辨率影像的细节信息上有所改善。 相似文献
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针对传统多光谱与全色影像融合方法容易产生畸变、忽略多光谱影像本身的空间细节特征等问题,提出了一种基于超分辨率卷积神经网络与Curvelet变换的影像融合方法,以提升多光谱影像的空间细节,加强其与全色影像的相关性,减少融合产生的畸变。该方法首先利用高分辨率全色影像进行超分辨率重建学习,利用学习得到的网络参数对多光谱影像进行超分辨率卷积神经网络重建,提升其空间细节特征;其次,在Gram-Schmid变换融合基础上,根据Curvelet变换具有保持影像空间细节的特点,将全色影像与替换分量进行融合;最后,通过逆变换得到高分辨率遥感影像。实验结果表明,该算法在影像光谱信息和空间细节表达能力上,整体优于其他传统算法,且对不同数据具有很好的适应性。 相似文献
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随着遥感获取数据手段的日益增多,遥感影像的融合技术备受关注。针对ASTER多光谱影像光谱信息丰富、分辨率小,资源二号全色影像分辨率高、纹理信息丰富的特点,以安徽省马鞍山市当涂县的ASTER多光谱影像与资源二号全色影像为例,分别采用基于主成分分析、小波变换以及主成分分析与小波变换相结合的3种融合方法进行融合实验,并对融合后的影像进行对比,探讨ASTER多光谱影像与资源二号全色影像融合的方法和效果。结果表明:采用主成分分析与小波变换相结合的方法对两幅影像融合的效果最好,极大地改善了两种单一方法的缺点,提高了原始影像的目视效果和光谱信息,从而为区域研究提供了更精确的数据资料。 相似文献
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一种自适应的基于局部小波系数特征的遥感图像融合方法 总被引:1,自引:0,他引:1
光谱保持和高分辨率保留是影像融合的两个重要问题。本文提出了一种自适应的基于局部小波系数特征的遥感影像融合方法。该方法在对多光谱影像进行IHS变换的基础上,对多光谱的I分量和高分辨率的全色影像分别进行小波多分辨率分析,而后对分解得到的近似分量以及各层各方向的细节分量利用移动模板逐一提取对应的小波系数矩阵的局部特征,采用本文提出的自适应融合准则在小波域进行影像融合,最后通过小波逆变换得到新的I′分量,与H,S分量一起还原到RGB空间,最终得到融合后的高分辨率多光谱彩色图像。本文采用一组TM多光谱图像和SPOT全色图像数据进行融合实验,利用标准差、熵,光谱扭曲度等5个重要评价指标对融合效果进行数理分析。其实验融合图像的目视效果和统计指标均优于IHS融和方法和小波融合方法。 相似文献
11.
M. J. McDONNELL D. PAIRMAN A. D. W. FOWLER 《International journal of remote sensing》2013,34(6):883-886
The Remote Sensing Section of the Physics and Engineering Laboratory has developed a general purpose image processing system. An overview of the system is given here. Its primary use is the production of special purpose map products from multispectral imagery. Its capabilities include enhancement, rectification, mosaicking, map digitization, automatic relief shading, filtering, restoration, classification and film production. The data base includes images from the LANDSAT and CZCS multispectral scanner satellites, images from an eleven-band aircraft multispectral scanner and a variety of digitized maps. 相似文献
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Kazuki Uehara Hirokazu Nosato Masahiro Murakawa Ryosuke Nakamura Hiroki Miyamoto Hidenori Sakanashi 《International journal of remote sensing》2013,34(2):752-771
ABSTRACTAn automatic object-detection method is necessary to facilitate the efficient analysis of satellite images consisting of multispectral images. Considering that the relationship between spectrums is important for discriminating objects in multispectral images. This paper proposes a feature extraction method that can capture both spatial and spectral relationships of the multispectral images. Moreover, image preprocessing and dimensionality reduction procedures are introduced for stable feature extraction. In this study, we conducted experiments for detecting two types of objects by using Landsat 8 images. The proposed method improved the detection performance relative to other image features. 相似文献
14.
K. Yu. Gorokhovskiy V. Yu. Ignatiev A. B. Murynin K. O. Rakova 《Journal of Computer and Systems Sciences International》2017,56(6):1008-1020
A probabilistic method for improving the spatial resolution of multispectral space images using a reference image is proposed. The developed method calculates the mathematical expectation of pixel brightness in different channels of an improved multispectral image based on the probabilistic characteristics of the pixel neighborhood on the multispectral image and the overall brightness intensity of the panchromatic image at that point. The applicability of different metrics for evaluating the quality of the spatial resolution of satellite images is analyzed. A set of the most adequate quality evaluation metrics is used. An optimization procedure is developed to adjust the parameters of the proposed probabilistic resolution improvement method. The results of testing the method on the multi-spectral images obtained from different satellites in different spatial resolutions are presented. The efficiency of the algorithm is tested at different magnification scales. A comparative analysis of the results of the proposed method with similar approaches is conducted. 相似文献
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历史航空影像客观有效地记录了自然景观与人文景观的演化变迁过程,是人类进行资源环境问题研究和改造客观现实世界的基础信息资源,从而为社会进步和可持续发展提供科学的决策支持。针对历史航空影像数字化与数据库建设工作的技术要求,通过对历史航空影像资料数字化作业规程的分析与探讨,给出了实用有效的历史航空影像数字化作业流程和技术指标,进而提出了切实可行的数字化历史航空影像建库技术路线和解决方案,并以历史航空影像数字化与建库试验研究验证了技术方案的合理性和可操作性,为历史航空影像数据库的建设提供前期的试验指导。 相似文献
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Tanakorn Sritarapipat Preesan Rakwatin 《International journal of remote sensing》2013,34(13):5120-5147
This article presents a new method for the fusion and registration of THEOS (Thailand Earth Observation Satellite) multispectral and panchromatic images in a single step. In the usual procedure, fusion is an independent process separated from the registration process. However, both image registration and fusion can be formulated as estimation problems. Hence, the registration parameters can be automatically tuned so that both fusion and registration can be optimized simultaneously. Here, we concentrate on the relationship between low-resolution multispectral and high-resolution panchromatic imagery. The proposed technique is based on a statistical framework. It employs the maximum a posteriori (MAP) criterion to jointly solve the fusion and registration problem. Here, the MAP criterion selects the most likely fine resolution multispectral and mapping parameter based on observed coarse resolution multispectral and fine resolution panchromatic images. The Metropolis algorithm was employed as the optimization algorithm to jointly determine the optimum fine resolution multispectral image and mapping parameters. In this work, a closed-form solution that can find the fused multispectral image with correcting registration is also derived. In our experiment, a THEOS multispectral image with high spectral resolution and a THEOS panchromatic image with high spatial resolution are combined to produce a multispectral image with high spectral and spatial resolution. The results of our experiment show that the quality of fused images derived directly from misaligned image pairs without registration error correction can be very poor (blurred and containing few sharp edges). However, with the ability to jointly fuse and register an image pair, the quality of the resulting fused images derived from our proposed algorithm is significantly improved, and, in the simulated cases, the fused images are very similar to the original high resolution multispectral images, regardless of the initial registration errors. 相似文献
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分析并改进了利用自组织特征映射(SOFM)神经网络设计码书的方法,提出了一种基于改进SOFM算法设计码书的矢量量化和分类谱间预测相结合的多光谱图像无损压缩方法。该方法对光谱信息进行矢量量化,根据分类信息生成残差图像以去除数据的空间相关性,构造分类谱间预测器去除数据的谱间结构和统计相关性。对机载64波段多光谱遥感图像的试验结果表明,该方法无论是对训练集内图像还是训练集外图像,均取得了较好的压缩效果,平均无损压缩比达到3.2以上。 相似文献
18.
基于整数小波变换的机载多光谱图像无损压缩 总被引:4,自引:0,他引:4
首先探讨了基于提升方案的整数小波变换,结合线性预测技术,提出了一种机载多光谱遥感图像的无损压缩方法。该方法通过整数小波变换减少图像的空间冗余,然后根据多光谱图像谱间的相关性对整数小波变换后的结果进行预测,并且加进了相关性判断这一环节保证了预测的有效性。算法适合并行处理和硬件实现。对机载64波段多光谱遥感图像的试验结果表明,该方法与改进的预测树方法相比其无损压缩比平均提高了16%,压缩时间缩短了三分之二。 相似文献
19.
Due to the performance limit of remote sensing systems, multispectral images have limited spatial resolution. Their spatial resolution can be improved by merging them with higher resolution image data. A fundamental problem frequently occurring in existing fusion processes, however, is the distortion of spectral information. This paper presents a spatially adaptive image fusion algorithm which produces visually natural images and retains the quality of local spectral information as well. High frequency information of the high resolution image to be inserted to the resampled multispectral images is controlled by adaptive gains to incorporate the difference of local spectral characteristics between the high and the low resolution images into the fusion. Each gain is estimated to minimize the l 2-norm of the error between the original and the estimated pixel values defined in a spatially adaptive window of which the weights are proportional to the spectral correlation measurements of the corresponding regions. This method is applied to a set of co-registered Landsat 7 Enhanced Thematic Mapper (ETM)+ panchromatic and multispectral image data. The experimental results show that high resolution images can be synthesized by the proposed method, which successfully preserves spectral content of the multispectral images. 相似文献
20.
P. Gong S. A. Mahler G. S. Biging D. A. Newburn 《International journal of remote sensing》2013,34(6):1303-1315
Using airborne multispectral digital camera imagery, we compared a number of feature combination techniques in image classification to distinguish vineyard from non-vineyard land-cover types in northern California. Image processing techniques were applied to raw images to generate feature images including grey level co-occurrence based texture measures, low pass and Laplacian filtering results, Gram-Schmidt orthogonalization, principal components, and normalized difference vegetation index (NDVI). We used the maximum likelihood classifier for image classification. Accuracy assessment is performed using digitized boundaries of the vineyard blocks. The most successful classification as determined by t-tests of the Kappa coefficients was achieved based on the use of a texture image of homogeneity obtained from the near infrared image band, NDVI and brightness generated through orthogonalization analysis. This method averaged an overall accuracy of 81 per cent for six frames of images tested. With post-classification morphological processing (clumping and sieving) the overall accuracy was significantly increased to 87 per cent (with a confidence level of 0.99). 相似文献