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检索条件"任意字段=Conference on Image Processing and Pattern Recognition in Remote Sensing"

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Alenia Aerospazio activity on SAR data analysis and information extraction

Alenia Aerospazio activity on SAR data analysis and informat...

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

作者： Ferrara, MN Torre, A Alenia Aerosp I-00131 Rome Italy

ISBN: (纸本)0819426490

Since the last few years some works have been presented, in open literature, in the field of SAR data analysis and information extraction. The more the SAR data become of common and routine usage, the more the need for automation of the interpretation and information extraction process increases. Alenia Aerospazio has started, in 1994, an R&D activity for the definition and implementation of a demonstrator of a system for SAR data analysis and automatic target recognition (ATR). The work has proceeded with the identification and selection of the basic tools for SAR image pre-processing (image co-registration, filtering, segmentation and backscattering reconstruction). The last step was the definition of the architecture of the ATR system. The considered architecture is based on a two-step process that can be run in sequence or separately. For single image input a rule-based system is considered. Rules for the identification of a predefined set of targets are under implementation. For a temporal series of input images a change-detection approach is considered. This last part of the work is in a preliminary stage: only the algorithm flow and routines identification task has been completed. The possible implementation of the system on a massively parallel computer is considered as a final goal.

关键词： SAR SAR image interpretation ATR

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Model based recognition and classification for surface texture of vegetation from aerial sequence of images

Model based recognition and classification for surface textu...

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conference on Earth Surface remote sensing

作者： Chen, HJ Houkes, Z Twente Univ Technol Fac Elect Engn Dept Control Syst & Comp Engn Lab Measurement & Instrumentat NL-7500 AE Enschede Netherlands

ISBN: (纸本)0819426547

In this paper, a model based recognition and classification method for surface texture of vegetation from aerial sequence of images is presented. The image sequences are assumed to be acquired by a video camera (RGB-CCD system) from an aeroplane, which moves linearly over the scene. The objects in the scenes being considered in this paper, are agricultural fields. The classes of agricultural fields to be distinguished are determined by the type of crop, e.g. potatoes, sugar beet, wheat etc. In order to recognize and classify these fields from aerial sequence of images, a common approach is in the use of surface texture. Here the Circular Symmetric Auto-Regressive(CSAR) random model is used for texture analysis. By manipulating the estimated value against its real value, the characteristics of a texture image may be determined. A hypothesize-and-verify algorithm is used for model recognition. Based on all kinds of models, classification for surface texture of vegetation from aerial sequences of images is realized.

关键词： aerial sequences of images texture of vegetation model based classification pattern recognition

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Block rotation: Implementation and applications

Block rotation: Implementation and applications

引用

conference on Parallel and Distributed Methods for image processing

作者： Fatemi, O Panchanathan, S Univ. of Ottawa (Canada) Univ. of Ottawa (United States)

ISBN: (纸本)0819425885

Visual media processing is becoming increasingly important because of the wide variety of image and video based applications. Block rotation is an important operation in different image/video processing tasks such as graphics, fractal processing, pattern matching and image registration. remote sensing, medical imaging, computer vision, computer graphics, and video coding are typical applications of digital image rotation. However, a hardware implementation of the block rotation algorithm has not been realized and software implementation is slow. Hence, they are not suitable for real-time execution. In this paper, we propose a novel method for block rotation, which is fast and suitable for hardware implementation. The algorithm employs area based interpolation. Experimental results have shown the performance enhancement compared to classical interpolation algorithms at a similar level of complexity.

关键词： image rotation spatial transformation affine transform interpolation forward mapping and backward mapping

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Region growing Euclidean distance transforms 9th

Region growing Euclidean distance transforms

引用

9th International conference on image Analysis and processing, ICIAP 1997

作者： Cuisenaire, Olivier Telecommunication and Remote Sensing Laboratory Université Catholique de Louvain Belgium

ISBN: (纸本)3540635076

By propagating a vector for each pixel, we show that nearly Euclidean distance maps can be produced quickly by a region growing algorithm using hierarchical queues. Properties of the propagation scheme are used to detect potentially erroneous pixels and correct them by using larger neighbourhoods, without significantly affecting the computation time. Thus, Euclidean distance maps are produced in a time comparable to its commonly used chamfer approximations. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Pixels

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Artificial immune systems and aerial image segmentation

Artificial immune systems and aerial image segmentation

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Proceedings of the 1997 IEEE International conference on Systems, Man, and Cybernetics. Part 1 (of 5)

作者： McCoy, David F. Devarajan, Venkat Commercial Remote Sensing Systems Garland United States

This paper describes our initial investigations in applying artificial immune systems to feature segmentation in remotely sensed images. The current generation of commercial imaging satellites provides increased opportunities for automated image analysis due to the large volume of high resolution imagery they will produce. Artificial immune systems (AIS) are successful in other pattern recognition tasks and have several similarities to the aerial image classification problem. We use an AIS for road pixel identification and observe several areas for further development.

关键词： Neural networks

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recognition of suspects through 3D photographs

Recognition of suspects through 3D photographs

引用

conference on Investigative image processing

作者： Proesmans, M VanGool, L Defoort, F Katholieke Univ. Leuven (Belgium)

ISBN: (纸本)0819423440

A system is proposed that simultaneously captures the three-dimensional shape of a face and its surface texture. Such a three-dimensional model allows to compare surveillance images of an offender irrespective of the pose of the offender's head. Also a single model for face albedo has been elaborated and its use will be demonstrated for viewing under different lighting conditions. The 3D acquisition system is based on an active technique, i.e. special illumination, but in contrast to traditional active sensing does not require scanning or sequential projection of multiple patterns. As a consequence, 3D photographs can be taken from a single image, and thus also when suspects do not collaborate.

关键词： Cameras 3D modeling Calibration Projection systems 3D image processing 3D acquisition Photography Reflectivity Head Imaging systems

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Contribution of lineament pattern analysis from Landsat TM data to a geomorphological-structural study of the Alpine-Dinaric domain

Contribution of lineament pattern analysis from Landsat TM d...

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conference on Earth Surface remote sensing

作者： Pepe, M Colombo, R Zilioli, E CNR IRRS Telerilevamento I-20133 Milan Italy

ISBN: (纸本)0819426547

In this study geological and geomorphological remote sensing investigation methodologies were applied to define the role of tectonic and neotectonic features in controlling the evolution of the Triest Karst territory, located at the Italian-Slovenian border. A Landsat TM image of the study area, has been visually interpreted using different products, with different information content, resulting from standard processing, in order to recognise main textural and structural characteristics of the area. The processing was aimed to enhance morphological (drainage networks, landmass denudation stages) and structural features (lineament pattern), as well as to identify main land-systems. Morphological, structural and landform elements were integrated to define some geomorphological-structural units having their own specific attributes. Structural trends have been recognised by means of rose diagram representations of lineament azimuth-frequency and cumulative-length distributions. Analysis of lineament frequency data, performed individually on each geomorphological-structural unit and on the study area as a whole, reveals that structural trends are strictly unit-dependent, and generally in agreement with regional structural models and focal mechanisms solutions reported in literature, with NE-SW dominant meso-alpine thrust faults reactivated with transpressive components during the neo-alpine phase and with more relevant dextral strike-slip movements recently, consistently with a NNW movement of the subthrusting Adria Plate, and an hypothetical counterclockwise rotation of the Istria peninsula.

关键词： Earth observing sensors Landsat Visualization Aluminium phosphide Statistical analysis Carbonates Data modeling Visual analytics Satellite imaging Satellites

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Fuzzy image classification using multiresolution neural networks with applications to remote sensing

Fuzzy image classification using multiresolution neural netw...

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Proceedings of the 1997 13th International conference on Digital Signal processing, DSP. Part 2 (of 2)

作者： Avrithis, Yannis S. Kollias, Stefanos D. Natl Technical Univ of Athens Zographou Greece

Recent progress in supervised image classification research, has demonstrated the potential usefulness of incorporating fuzziness in the training, allocation and testing stages of several classification techniques. In this paper a multiresolution neural network approach to supervised classification is presented, exploiting the inherent fuzziness of such techniques in order to perform classification at different resolution levels and gain in computational complexity. In particular, multiresolution image analysis is carried out and hierarchical neural networks are used as an efficient architecture for classification of the derived multiresolution image representations. A new scheme is then introduced for transferring classification results to higher resolutions based on the fuzziness of the results of lower resolutions, resulting in faster implementation. Experimental results on land cover mapping applications from remotely sensed data illustrate significant improvements in classification speed without deterioration of representation accuracy.

关键词： Object recognition

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Concealed weapon detection: An image fusion approach

Concealed weapon detection: An image fusion approach

引用

conference on Investigative image processing

作者： Uner, MK Ramac, LC Varshney, PK Alford, M Syracuse Univ. (United States) Rome Lab. (United States)

ISBN: (纸本)0819423440

This paper presents an approach to image fusion for concealed weapon detection (CWD) applications. In this work, we use image fusion to combine complementary image information from different sensors to obtain a single composite image with more detailed and complete information content. As a result of this processing, the new images are more useful for human perception and automatic computer analysis, tasks such as feature extraction and object recognition. In the fusion process, the images are first decomposed based on wavelet transform. Then at each lower resolution the images are fused by using several feature selection algorithms. The final composite image is obtained by taking the inverse wavelet transform of the fused wavelet coefficients. This technique has been applied to real data obtained from IR sensors. Special emphasis is placed on situations when weapons may not be completely visible from the sensors. Fusion results thadt demonstrate the utility of our approach are presented.

关键词： image fusion wavelets multiresolution analysis image decomposition concealed weapon detection multisensor systems multiscale image processing sensor fusion

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image enhancement and denoising by wavelet transform for concealed weapon detection

Image enhancement and denoising by wavelet transform for con...

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conference on Investigative image processing

作者： Raghuveer, MR Rochester Institute of Technology (United States)

ISBN: (纸本)0819423440

Wavelet transform based techniques were developed and investigated for isolation and enhancement of objects in images. The primary motivation is the development of image processing algorithms as part of an automatic system for the detection of concealed weapons under a person's clothing;a problem of considerable potential utility to the military in certain common types of deployment in the post cold war environment such as small unit operations. The issue has potential for other dual use purposes such as law enforcement applications. Wavelet decompositions of the currently available images in the Rome Laboratory database, namely, noisy, low contrast, infrared images, were studied in space-scale-amplitude space. An isolation technique for separating potential suspicious regions/objects from surrounding clutter has been proposed. Based on the images available, the study indicates that the technique is promising in providing the image enhancement necessary for further pattern detection and classification.

关键词： Weapons image enhancement Discrete wavelet transforms Sensors Wavelet transforms Infrared sensors Algorithm development Digital image processing Infrared imaging Wavelets

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