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conference on image and signal processing for remote sensing xviii

作者： Harikumar, V. Joshi, Manjunath V. Raval, Mehul S. Gajjar, Prakash P. Dhirubhai Ambani Inst Informat & Commun Technol Gandhinagar Gujarat India

ISBN: (纸本)9780819492777

Multiresolution fusion refers to the enhancement of low spatial resolution (LR) of multispectral (MS) images to that of panchromatic (Pan) image without compromising on the spectral details. Many of the present day methods for multiresolution fusion require that the Pan and MS images are registered. In this paper we propose a new approach for multiresolution fusion which is based on the theory of compressive sensing and graph cuts. We first estimate a close approximation to the fused image by using the sparseness in the given Pan and MS images. Assuming that they have the same sparseness, the initial estimate of the fused image is obtained as the linear combination of the Pan blocks. The weights in the linear combination are estimated using the l 1 minimization by making use of MS and the down sampled Pan image. The final solution is obtained by using a model based approach. The low resolution MS image is modeled as the degraded and noisy version of the fused image in which the degradation matrix entries are estimated by using the initial estimate and the MS image. Since the MS fusion is an ill-posed inverse problem, we use a regularization based approach to obtain the final solution. A truncated quadratic smoothness prior is used for the preservation of the discontinuities in the fused image. A suitable energy function is then formed which consists of data fitting term and the prior term and is minimized using a graph cuts based approach in order to obtain the fused image. The advantage of the proposed method is that it does not require the registration of Pan and MS data. The spectral characteristics are well preserved in the fused image since we are not directly operating on the Pan digital numbers. Effectiveness of the proposed method is illustrated by conducting experiments on synthetic as well as on real satellite images. Quantitative comparison of the proposed method in terms of Erreur Relative Globale Adimensionnelle de Synthase (ERGAS), Correlation Coeffici

关键词： Multiresolution image fusion Compressive sensing Graph cuts

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Review of Research on Registration of SAR and Optical remote sensing image Based on Feature 3

Review of Research on Registration of SAR and Optical Remote...

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IEEE 3rd International conference on signal and image processing (ICSIP)

作者： Li Kai Zhang Xueqing Natl Univ Def Technol Informat & Commun Engn Coll Wuhan Hubei Peoples R China

ISBN: (纸本)9781538663967

Synthetic Aperture Radar(SAR) and optical remote sensing image registration is the prerequisite for image fusion and it is of important theoretical significance and practical value. The image registration methods are mainly divided into the methods based on feature, the methods based on Gray-scale and others. This article systematically sorts out feature-based optical and SAR remote sensing image registration techniques, summarizes all types of image registration, points out their advantages and disadvantages and predicts the prospects of their future.

关键词： synthetic aperture radar(SAR) remote sensing image registration feature-based

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Zero-watermarking for Copyright Protection of remote sensing image

Zero-watermarking for Copyright Protection of Remote Sensing...

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9th International conference on signal processing

作者： Jing, Li Zhang, Yadong Chen, Guangyu Henan Univ Finance & Econ Coll Informat Zhengzhou 450002 Peoples R China

ISBN: (纸本)9781424421787

Watermarking technique is the main method for copyright protection. But this technique does not suit remote sensing image because the embedded watermark heavily affects the results of its applicative tasks. In order to protect remote sensing image, this paper proposes a robust zero-watermarking method that constructs watermarks from the host data instead of embedding watermark into that data. The proposed method constructs two watermarks from host image. One is constructed from low-frequency coefficients in discrete wavelet transform domain of the host image, and the other is constructed from that of the log-polar mapping image of the host image. Experiments show that this method is robust to both signal processes and geometrical distortions.

关键词： Discrete wavelet transforms

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MVITP: MULTI-VIEW image-TEXT PERCEPTION FOR FEW-SHOT remote sensing image CLASSIFICATION 49

MVITP: MULTI-VIEW IMAGE-TEXT PERCEPTION FOR FEW-SHOT REMOTE ...

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49th IEEE International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Yang, Chen Liu, Tongtong Jiao, Didi Li, Wenhui Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Few-shot learning has been extensively applied in current remote sensing image classification, enabling rapid identification of new classes by leveraging prior knowledge effectively. However, current methods mainly rely on image modality to address the issue of low intra-class similarity and high interclass similarity, while the utilization of multimodal methods in remote sensing tasks remains largely unexplored. Therefore, we propose a novel framework for few-shot remote sensing image classification, named multi-view image-text perception (MVITP). Specifically, it leverages maximum mutual information across multiple views to train an image encoder and generate image features. A text encoder is employed to generate text features. Next, we introduce a multimodal fusion encoder to capture the similarity between image features and text features. Finally, class predictions are further made by computing the similarity between the support set and the query set. We conduct experiments on three remote sensing datasets, demonstrating the outstanding performance of MVITP.

关键词： Maximum mutual information multimodal fusion few-shot learning remote sensing image classification

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Aircraft Segmentation from remote sensing image by Transferring Natual image Trained Forground Extraction CNN Model 4

Aircraft Segmentation from Remote Sensing Image by Transferr...

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4th IEEE International conference on signal and image processing (ICSIP)

作者： Zeng, Yanqing Niu, Xin Dou, Yong Natl Univ Def Technol Dept Comp Changsha Hunan Peoples R China

ISBN: (纸本)9781728136608

With the rapid development of remote sensing technology, remote sensing image processing has been widely used in the field of national defense and the people's livelihood. However, due to the high cost of manually collecting and annotating data, the number of currently public remote sensing datasets are limited, and the datasets of remote sensing images for foreground segmentation and detection is also confined. In this paper, because of the difficulty of small-sized datasets, the foreground segmentation of aircraft remote sensing image is realized by using the idea of transfer learning. We implemented three kinds of different aircraft segmentation networks for small-sized aircraft remote sensing images by transferring three kinds of different foreground segmentation networks trained on large-scaled datasets. The best aircraft segmentation accuracy is up to 79.201% under custom evaluation criteria. Experiment results showed that transferring a foreground extraction CNN model trained on public datasets to cope with the task of aircraft segmentation on small aircraft remote sensing images is significantly effective.

关键词： Foreground segmentation remote sensing images Transfer learning Deep learning

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Computationally efficient strategies to perform anomaly detection in hyperspectral images

Computationally efficient strategies to perform anomaly dete...

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conference on image and signal processing for remote sensing xviii

作者： Rossi, Alessandro Acito, Nicola Diani, Marco Corsini, Giovanni Univ Pisa Dipartimento Ingn Informaz Via G Caruso 16 I-56122 Pisa Italy Accad Navale Livorno I-57100 Livorno Italy

ISBN: (纸本)9780819492777

In remote sensing, hyperspectral sensors are effectively used for target detection and recognition because of their high spectral resolution that allows discrimination of different materials in the sensed scene. When a priori information about the spectrum of the targets of interest is not available, target detection turns into anomaly detection (AD), i.e. searching for objects that are anomalous with respect to the scene background. In the field of AD, anomalies can be generally associated to observations that statistically move away from background clutter, being this latter intended as a local neighborhood surrounding the observed pixel or as a large part of the image. In this context, many efforts have been put to reduce the computational load of AD algorithms so as to furnish information for real-time decision making. In this work, a sub-class of AD methods is considered that aim at detecting small rare objects that are anomalous with respect to their local background. Such techniques not only are characterized by mathematical tractability but also allow the design of real-time strategies for AD. Within these methods, one of the most-established anomaly detectors is the RX algorithm which is based on a local Gaussian model for background modeling. In the literature, the RX decision rule has been employed to develop computationally efficient algorithms implemented in real-time systems. In this work, a survey of computationally efficient methods to implement the RX detector is presented where advanced algebraic strategies are exploited to speed up the estimate of the covariance matrix and of its inverse. The comparison of the overall number of operations required by the different implementations of the RX algorithms is given and discussed by varying the RX parameters in order to show the computational improvements achieved with the introduced algebraic strategy.

关键词： hyperspectral images anomaly detection RX algorithm real-time processing

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Perspectives and visions for future SAR systems

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IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION 2003年第3期150卷 97-103页

作者： Keydel, W DLR Microwaves & Radar Inst D-82230 Wessling Germany

It is shown how far new SAR techniques, technologies and system principles, which at present are under consideration or under development, respectively, will fulfil future user requirements. Starting from the status quo, the expected development of future SAR techniques and technology is presented, leading to the vision of an autonomous, global reconnaissance and remote sensing system with integrated communication and positioning capability. This system will have central illuminators together with a synchronised fleet of both airborne and spaceborne receivers, which enable continuous availability with a nearly global coverage, and dedicated information transfer to specific users in real time.

关键词： SAR techniques real time information transfer airborne radar Radar theory SAR technology spaceborne radar global reconnaissance system remote sensing by radar spaceborne SAR radar receivers Radar equipment, systems and applications technological forecasting spaceborne receivers Optical, image and video signal processing airborne receivers radar imaging integrated communication-positioning system SAR systems synthetic aperture radar global remote sensing system global coverage real-time SAR signal processing

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Wavelets - a universal tool for the processing of remote sensing image data?

Wavelets - a universal tool for the processing of remote sen...

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conference on image processing, signal processing, and Synthetic Aperture Radar for remote sensing

作者： Schwarz, G Datcu, M DLR German Remote Sensing Data Ctr German Aerosp Res Estab DFD D-82234 Oberpfaffenhofen Germany

ISBN: (纸本)0819426490

During the last years, wavelets have become very popular in the fields of signal processing and pattern recognition and have led to a large number of publications. In the discipline of remote sensing several applications of wavelets have emerged, too. Among them are such diverse topics as image data compression, image enhancement, feature extraction, and detailed data analysis. On the other hand, the processing of remote sensing image data-both for optical and radar data-follows a well-known systematic sequence of correction and data management steps supplemented by dedicated image enhancement and data analysis activities. In the following we will demonstrate where wavelets and wavelet transformed data can be used advantageously within the standard processing chain usually applied to remote sensing image data. Summarizing potential wavelet applications for remote sensing image data, we conclude that wavelets offer a variety of new perspectives especially for image coding, analysis, classification, archiving, and enhancement. However, applications requiring geometrical corrections and separate dedicated representation bases will probably remain a stronghold of classical image domain processing techniques.

关键词： wavelets image processing remote sensing radiometry geometry enhancement data management

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Transform methods for remote sensing environmental monitoring

Transform methods for remote sensing environmental monitorin...

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33rd IEEE International conference on Acoustics, Speech and signal processing

作者： Chen, Chi Hau Univ Massachusetts Dept Elect & Comp Engn N Dartmouth MA 02747 USA

ISBN: (纸本)9781424414833

Transform methods in signal and image processing generally speaking are easy to use and can play a number of useful roles in remote sensing environmental monitoring. Examples are the pollution and forest fire monitoring. Transform methods offer effective procedures to derive the most important information for further processing or human interpretation and to extract important features for pattern classification. Most transform methods are used for image (or signal) enhancement and compression. However other transform methods are available for linear or nonlinear discrimination in the classification problems. In this paper we will examine the major transform methods which are useful for remote sensing especially for environmental monitoring problems. Many challenges to signal processing will be reviewed. Computer results are shown to illustrate some of the methods discussed.

关键词： transform methods environmental monitoring SAR image noise component analysis contextual image models

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remote-sensing image fusion based on multiwavelet transform and IHS transform

Remote-sensing image fusion based on multiwavelet transform ...

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8th International conference on signal processing

作者： Wang, Tianpeng Li, Bicheng Yu, Chaoqun Cao, Wen Zhengzhou Informat Sci & Technol Inst Zhengzhou 450002 Peoples R China Inst Surveying & Mapping Zhengzhou 450002 Peoples R China

ISBN: (纸本)9780780397361

Multiwavelet transform is a new development to the wavelet theory. It can offer orthogonality, symmetry, and short support simultaneously, and can offer a more precise way for image analysis than wavelet multi-resolution. A now remote-sensing image fusion method based on intensity-hue-saturation transform(IHST) and Mulliwavelet Transform(MWT) is presented to fusion a multi-spectral image and a panchromatic image. Firstly, the multi-spectral image is transformed with IHST;Secondly, the panchromatic image and I component of the multi-spectral image are merged with MWT-based fusion method, and I component is replaced with the merged data;finally, the fused image is obtained by inverse IHST. Comparing with other methods, the new method can enhance spatial detail information of remote-sensing images largely and provide more spatial information at the same time.

关键词： remote-sensing image fusion IHS transform multiwavelet transformation

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