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1.
Remote Sensing Image Segmentation with Probabilistic Neural Networks   总被引:3,自引:0,他引:3  
This paper focuses on the image segmentation with probabilistic neural networks (PNNs). Back propagation neural networks (BpNNs) and multi perceptron neural networks (MLPs) are also considered in this study, Especially, this paper investigates the implementation of PNNs in image segmentation and optimal processing of image segmentation with a PNN. The comparison between image segmentations with PNNs and with other neural networks is given. The experimental results show that PNNs can be successfully applied to image segmentation for good results.  相似文献   

2.
Linear quadtree is a popular image representation method due to its convenient imaging procedure. However, the excessive emphasis on the symmetry of segmentation, i.e. dividing repeatedly a square into four equal sub-squares, makes linear quadtree not an optimal representation. In this paper, a no-loss image representation, referred to as Overlapped Rectangle Image Representation (ORIR), is presented to support fast image operations such as Legendre moments computation. The ORIR doesn't importune the symmetry of segmentation, and it is capable of representing, by using an identical rectangle, the information of the pixels which are not even adjacent to each other in the sense of 4-neighbor and 8-neighbor. Hence, compared with the linear quadtree, the ORIR significantly reduces the number of rectangles required to represent an image. Based on the ORIR, an algorithm for exact Legendre moments computation is presented. The theoretical analysis and the experimental results show that the ORIR-based algorithm for exact Legendre moments computation is faster than the conventional exact algorithms.  相似文献   

3.
4.
The German CHAlleging Minisatellite Payload (CHAMP) was launched in July 2000. It is the first satellite that provides us with position and accelerometer measurements, with which the gravity field model can be determined. One of the most popular methods for geopotential recovery using the position and accelerometer measurements of CHAMP is the energy conservation method, The main aim of this paper is to determine the scale and bias parameters of CHAMP accelerometer data using the energy conservation method. The basic principle and mathematical model using the crossover points of CHAMP orbit to calibrate the accelerometer data are given based on the energy balance method. The rigorous integral formula as well as its discrete form of the observational equation is presented, This method can be used to estimate only one of the scale and bias parameters or both of them. In order to control the influence of outliers, the robust estimator for the calibration parameters is given. The results of the numerical computations and comparisons using the CHAMP accelerometer data show the validity of the method.  相似文献   

5.
Designing detection algorithms with high efficiency for Synthetic Aperture Radar(SAR) imagery is essential for the operator SAR Automatic Target Recognition(ATR) system.This work abandons the detection strategy of visiting every pixel in SAR imagery as done in many traditional detection algorithms,and introduces the gridding and fusion idea of different texture fea-tures to realize fast target detection.It first grids the original SAR imagery,yielding a set of grids to be classified into clutter grids and target grids,and then calculates the texture features in each grid.By fusing the calculation results,the target grids containing potential maneuvering targets are determined.The dual threshold segmentation technique is imposed on target grids to obtain the regions of interest.The fused texture features,including local statistics features and Gray-Level Co-occurrence Matrix(GLCM),are investigated.The efficiency and superiority of our proposed algorithm were tested and verified by comparing with existing fast de-tection algorithms using real SAR data.The results obtained from the experiments indicate the promising practical application val-ue of our study.  相似文献   

6.
SAR image classification based on its texture features   总被引:2,自引:2,他引:0  
SAR images not only have the characteristics of all-ay, all-eather, but also provide object infor-mation which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The au-thors conducted the experiments of texture statistics analysis on SAR im-age features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpreta-tion.  相似文献   

7.
基于经验模态分解的高分辨率影像融合(英文)   总被引:3,自引:0,他引:3  
High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition (EMD). The intensity hue saturation (IHS) transform of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After presenting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion technique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function (IMF) for the merger on the basis of EMD analysis on specific row (column) pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms (wavelet, IHS, Brovey). The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience.  相似文献   

8.
House change detection based on DSM of aerial image in urban area   总被引:1,自引:1,他引:0  
The change of house often brings on the change of DSM in an area over different periods. If we can apply information of the height of houses to reinforce the house change detection, the reliability and efficiency of detection methods will be improved greatly.From this viewpoint, a new approach taking advantage of both height data from an image pair and image data is proposed to detect the house change in urban area and is called "data fusion technology".  相似文献   

9.
Application of GIS to estimate soil erosion using RUSLE   总被引:9,自引:0,他引:9  
This paper describes the use of the Arc/Info and ArcView GIS tools to estimate soil erosion with Universal Soil Loss Equation (USLE).Calculations are be done by using capabilities available.This study start with a digital elevation model(DEM) of Shaanxi,which was created by digitizing contour and spot heights from the topographic map on 1:250000 scale and grid themes for the USLE K and C factors.It is note worthy that USLE K can be obtained by adding the K factor as an attribute to a soil theme‘s table.The C can be obtained from tables or using the information about land use and management given by USLE program.A land use theme can be used to add the C factors as an attribute field.The purpose of this study is to establish spatial information of soil erosion using USLE and GIS and discuss the analysis of the soil erosion and slope failures in GIS and formulate the possible framework.  相似文献   

10.
An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.  相似文献   

11.
介绍了一种非线性扩散过滤器法从包含纹理的图像中获取灰度、尺度和方向信息,并形成经过耦合保边平滑的5通道向量值图像,对纹理图像的分割变为对此向量值图像的分割。针对半自动操作的特点,在合理的假设前提下,采用了多通道统计区域分割法。试验结果表明,本文的纹理分割方法能有效地利用重要纹理特征与灰度的混合信息,是一种半自动的无监督纹理图像分割方法。  相似文献   

12.
提出一种二值马尔科夫纹理分割模型,用于多波段遥感影像的纹理分割.将一次性多类纹理分割问题转化为多次的二类纹理分割,综合考虑影像二维空间尺度和光谱空间尺度,采取多级二值分割的方式,得到多尺度纹理分割结果.  相似文献   

13.
针对遥感图像分割时仅利用光谱信息容易造成过分割和边缘定位不准的问题,提出一种结合光谱强度和纹理信息的遥感图像分水岭分割算法。首先分别提取图像的光谱梯度和纹理梯度,提出一种改进双边滤波模型,滤除图像中的噪声的周时,采用了一种局部的平滑尺度,能够有效消除纹理信息,借助于滤波算法,分别对原图像和Gabor纹理特征图像进行平滑处理,利用边缘检测算子得到光谱梯度和纹理梯度。最后利用形态学膨胀方法进行融合融合,使用分水岭变换对图像分割。用三幅高分辨率彩色遥感图像数据进行实验,并与JSEG(Joint Systems Engineering Group)和多分辨率分割方法进行比较,结果表明该方法具有较高的边界定位准确性,同时降低了过分割和欠分割现象。  相似文献   

14.
针对经典的小波纹理不能准确地表达影像纹理特征的问题,以及影像分割结果缺少对像元空间相关性和分布关系的考虑。本文提出了结合双树复小波(DT-CWT)纹理和马尔可夫随机场(MRF)模型的高分辨率遥感影像分割方法。首先,通过双树复小波变换提取影像纹理特征,联合光谱特征形成表达影像信息的混合特征向量;然后,将混合特征向量高斯归一化处理,并用K-means聚类的方法对特征空间中的混合特征向量聚类得到初始分割图;最后,借助马尔可夫随机场模型在初始分割结果中引入上下文信息,基于贝叶斯最大后验概率准则得到最终的分割结果。本文通过双树复小波纹理提高了特征表达的准确度,同时使用马尔可夫随机场模型减弱了分割结果中同质区域的“椒盐噪声”,从而进一步提高了高分辨率遥感影像分割的精度。  相似文献   

15.
侧扫声呐图像分割的中性集合与量子粒子群算法   总被引:1,自引:1,他引:0  
针对现有的侧扫声呐图像分割方法存在分割准确率不高和效率偏低的问题,提出了一种基于中性集合和量子粒子群算法的侧扫声呐图像阈值分割方法。通过基于中性集合计算图像灰度共生矩阵,实现了侧扫声呐图像精细纹理的表达,提高了分割精度;基于二维最大熵理论,采用量子粒子群算法计算二维最优分割阈值向量,实现了分割阈值向量的快速准确获取,提高了分割效率和精度。最终实现了高噪声侧扫声呐图像目标的准确、高效分割。通过对含有不同目标的侧扫声呐图像的分割试验,验证了该算法的有效性。  相似文献   

16.
韩冰  赵银娣  戈乐乐 《测绘学报》2013,42(2):233-238
由于已有小波域HMT(hidden Markov tree)图像分割算法在上下文融合阶段直接对数据块大小不等的相邻两尺度进行信息融合,导致细节信息分割不充分。为此,提出一种基于迭代上下文融合的小波域HMT模型图像分割算法。该算法在上下文融合阶段采用迭代融合方法,将每一尺度的融合结果作为该尺度的上下文信息再次融合,并设置变化阈值作为迭代终止条件。利用Brodatz纹理组合图像和Formosat-2遥感图像进行分割试验。定性和定量分析表明本文算法能改善图像分割的细节效果,进一步提高图像分割精度。  相似文献   

17.
珊瑚礁对于海洋生态环境研究具有重要意义,通过分析珊瑚礁底栖物质的分布及健康状况,可以对珊瑚礁生态环境进行评估。本文提出了一种基于面向对象的图像分类方法,通过试验确定不同地貌的最优分割尺度,其中陆地和深海的最优分割尺度为150,各类底栖物质的最优分割尺度为30。以Sentinel-2A卫星遥感影像为例,提取海南三亚珊瑚礁自然保护区的珊瑚礁底栖物质,并使用混淆矩阵对提取结果进行精度评估。结果表明,底栖物质提取总体分类精度为87.91%,Kappa系数为0.83。面向对象分类方法可有效结合珊瑚礁底栖物质的纹理特征和光谱特征,并充分利用遥感影像不同波段的组合特性,可为三亚珊瑚礁保护管理提供方法支撑。  相似文献   

18.
In this research, an object-oriented image classification framework was developed which incorporates nonlinear scale-space filtering into the multi-scale segmentation and classification procedures. Morphological levelings, which possess a number of desired spatial and spectral properties, were associated with anisotropically diffused markers towards the construction of nonlinear scale spaces. Image objects were computed at various scales and were connected to a kernel-based learning machine for the classification of various earth-observation data from both active and passive remote sensing sensors. Unlike previous object-based image analysis approaches, the scale hierarchy is implicitly derived from scale-space representation properties. The developed approach does not require the tuning of any parameter—of those which control the multi-scale segmentation and object extraction procedure, like shape, color, texture, etc. The developed object-oriented image classification framework was applied on a number of remote sensing data from different airborne and spaceborne sensors including SAR images, high and very high resolution panchromatic and multispectral aerial and satellite datasets. The very promising experimental results along with the performed qualitative and quantitative evaluation demonstrate the potential of the proposed approach.  相似文献   

19.
高分辨率影像的广泛应用推进面向对象影像分析(OBIA)的发展,而分割作为面向对象分类的关键步骤,其尺度的选择直接关系到地物信息的提取。空间尺度是地物的固有属性,在合适的分割尺度下可以更好地挖掘地物信息。本文结合最大面积法和分割质量评价模型对张山营镇影像进行分割实验,先通过分析对象最大面积初步得到最优尺度范围,后结合分割质量评价模型以确定最优分割尺度层次。在此基础上,综合样本提取的光谱、纹理等特征进行规则训练,最终完成面向对象的土地覆被分类研究。结果显示:基于多层次最优尺度的规则分类方法获得更好的分类结果,其总体精度为88.8%,Kappa系数为0.861,而基于单一尺度的最邻近法总体精度81.4%,Kappa系数0.773,基于单一尺度的规则分类法总体精度为83.2%,Kappa系数为0.85。  相似文献   

20.
根据基于区域增长的面向对象图像分割的本质特点,将统计学习理论与最小生成树算法相结合,提出了一种基于统计学习理论的最小生成树图像分割准则。将该图像分割准则应用于多种遥感影像数据进行分割实验,其结果表明基于统计学习理论的最小生成树图像分割准则能通过简便的参数设置,即可以较好地实现不同尺度目标的图像分割,同时又能对纹理区域进行有效分割,能获得良好的区域边界和较好的抗噪声性能,并在海岸带大比例尺无人机正射影像的图像分割实践中得到了较好验证。  相似文献   

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