With the ability of multiresolution analysis and image decomposition, the wavelet transform has been employed to remotesensingimage fusion. The multiresolution analysis of the discrete wavelet transform does not pre...
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ISBN:
(纸本)9780780397361
With the ability of multiresolution analysis and image decomposition, the wavelet transform has been employed to remotesensingimage fusion. The multiresolution analysis of the discrete wavelet transform does not preserve the translation invariance, and the undecimated discrete wavelet transform can resolve the nonstationarity through suppressing the downsampling operation. To fuse the multisensor remotesensingimage, a new method based on the hue-intensity-saturation transform, high pass filter and undecimated discrete wavelet transform is proposed. The TM multispectral image and the SPOT panchromatic image are experimented, and both subjectively qualitative analysis and objectively quantitative evaluation verify the performance of the new method.
In the last decade, the application of statistical and neural network classifiers to remote-sensingimages has been deeply investigated. Therefore, performances, characteristics, and pros and cons of such classifiers ...
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ISBN:
(纸本)081943826X
In the last decade, the application of statistical and neural network classifiers to remote-sensingimages has been deeply investigated. Therefore, performances, characteristics, and pros and cons of such classifiers are quite well known, even from remote-sensing practitioners. In this paper, we present the application to remote-sensingimage classification of a new pattern recognition technique recently introduced within the framework of the Statistical Learning Theory developed by V. Vapnik and his co-workers, namely, the Support Vector Machines (SVMs). In section 1, the main theoretical foundations of SVMs are presented. In section 2, experiments carried out on a data set of multisensor remote-sensingimages are described, with particular emphasis on the design and training phase of a SVM. In section 3, the experimental results are reported, together with a comparison between the performances of SVMs, neural network, and k-NN classifiers.
One of the key steps of automatic digital elevation model production from aerial photos or satellite remote sensed images is introducing a robust matching algorithm. In this paper a feature-based matching method is pr...
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ISBN:
(纸本)0819416452
One of the key steps of automatic digital elevation model production from aerial photos or satellite remote sensed images is introducing a robust matching algorithm. In this paper a feature-based matching method is presented. The characteristics of this algorithm are that: first, the matching input for the first matching procedure are the radiometric and geometric noise invariant properties of image patches;second, the local matching inputs are used for extrinsic optimal matching procedure (presently only for the scan line).
remotesensing has become an important resource for numerous areas of application. Efficient methods for analysis and visualization of this data are needed as new satellites with improved capabilities are planned and ...
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A on-board ship targets detection method based on multi-scale salience enhancement is proposed. Unlike the traditional wavelet filter enhancement methods, the proposed utilizes the wavelet decomposition to obtain the ...
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ISBN:
(纸本)9781509013456
A on-board ship targets detection method based on multi-scale salience enhancement is proposed. Unlike the traditional wavelet filter enhancement methods, the proposed utilizes the wavelet decomposition to obtain the high-low frequency parts, and estimate the salience feature with both parts, which enhance the ship targets efficiently. First, decompose the remotesensingimage by 2-D DWT, and obtain the low-frequency part, high-frequency part of horizontal, vertical and diagonal;then, compute the OSTU threshold, which is subtracted by the low-frequency coefficients to get the low-frequency salience image;and, the high-frequency parts are used to compose the high-frequency salience image;finally, the high-low parts are fused by addition and normalized to obtain the salience map. The original data of multi sets of remotesensingimages are experimented, and the results are compared with the method without the proposed salience enhancement. The proposed shows obvious salience enhancement for the low-resolution, high-noise remotesensingimages.
This article presents a method to generate ortho-images with digital elevation model and a few ground control points. The method has been integrated to take into account the geometric distortions of the full geometry ...
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ISBN:
(纸本)0819416452
This article presents a method to generate ortho-images with digital elevation model and a few ground control points. The method has been integrated to take into account the geometric distortions of the full geometry of viewing (sensor-platform-Earth), and unified to process images from different sensors (VIR and SAR) on various platforms (airborne and spaceborne). Results from eight types of images show an absolute accuracy of 1/3 of a pixel for VIR satellite images and one to two pixels for the other images (SAR and airborne), and a relative accuracy of one pixel between the image. Mosaicing of these ortho-images with the road network overlaid confirms the relative and absolute accuracies.
With the rapid scientific and technical advances in remotesensing, digital imageprocessing becomes an important tool for quantitative and statistical analysis of remotely sensed images. These images contain most oft...
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ISBN:
(纸本)0819416452
With the rapid scientific and technical advances in remotesensing, digital imageprocessing becomes an important tool for quantitative and statistical analysis of remotely sensed images. These images contain most often complex natural scenes. Robust interpretation of such images requires the use of different sources of information about the scenes under consideration. This paper presents our work on analyzing remotely sensed images by integrating multispectral data, map knowledge and contextual information. An overview of the approach is first described. Then the utilization of map knowledge to improve the effectiveness and robustness of urban area detection is explained in more details.
Support Vector Machines (SVM) have been widely adopted by the remotesensing community in the last decade. The standard algorithm has been mainly applied to image classification tasks. Many advanced developments based...
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ISBN:
(纸本)9780819488077
Support Vector Machines (SVM) have been widely adopted by the remotesensing community in the last decade. The standard algorithm has been mainly applied to image classification tasks. Many advanced developments based on SVM have been introduced as well. This paper, nevertheless, revises the standard formulation of SVM. An important part of the paper is about the intuition on the SVM parts: the cost, the regularizer and the free parameters. Finally, the paper revises three interesting simple modifications well suited to tackle remotesensingimage classification: constraining the margin, including invariances and the information of unlabeled samples. Some examples are given to illustrate these concepts.
This paper proposes a novel wavelet-based image fusion method that combines the selection and weighted average fusion rules for interpreting remotesensingimages. When the local variance of source images is various g...
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ISBN:
(纸本)9781467321969
This paper proposes a novel wavelet-based image fusion method that combines the selection and weighted average fusion rules for interpreting remotesensingimages. When the local variance of source images is various greatly, the fusion coefficient of images is obtained by the selection rule, otherwise it will be acquired by the weighted average rule. The new fusion rule both preserves the source images' detail and improves the algorithm stability. Experiment results demonstrate that the new fusion rule is effective.
image registration is the first step in many application areas such as computer vision, remotesensing and medical imageprocessing. image registration is achieved by aligning two or more images according to the estim...
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ISBN:
(纸本)9781424444731
image registration is the first step in many application areas such as computer vision, remotesensing and medical imageprocessing. image registration is achieved by aligning two or more images according to the estimated transformation between them. In this paper, we present an image registration algorithm, which combines the multi-scale wavelet transform with Scale Invariant Feature Transform (SIFT). First, images are decomposed into multiple scales using Wavelet Transform (WT), then the low frequency (approximation) image at certain level is input to SIFT algorithm. The proposed algorithm speeds up the calculation of the correspondences between images. Experimental results with different remotesensingimages illustrate the accuracy of proposed algorithm.
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