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检索条件"任意字段=Image Processing: Algorithms and Systems VI"

共 197 条记录，以下是61-70 订阅

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Hyperspectral Compressive Sensing

Hyperspectral Compressive Sensing

引用

Conference on Satellite Data Compression, Communications, and processing vi

作者： Lv, Jingyuan Li, Yunsong Huang, Bormin Wu, Chengke Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Univ Wisconsin Space Sci & Engn Ctr Madison WI 53706 USA

ISBN: (纸本)9780819483065

Compressive sensing (CS) is a new technique for reconstructing essentially sparse signals from a number of measurements smaller than the Nyquist-Shannon criterion. The application of CS to hyperspectral imaging has the potential for significantly reducing the sampling rate and hence the cost of the analog-to-digital sensors. In this paper a novel approach for hyperspectral compressive sensing is proposed where each band of hyperspectral imagery is sampled under the same measurement matrix. It is shown that the correlation between two neighboring band compressive sample values is consistent with that between two neighboring band pixel values. Our hyperspectral compressive sensing experimental results show that the proposed joint reconstruction method yields smaller reconstruction errors than the individual reconstruction method at various sampling rates.

关键词： Hyperspectral imaging image compression Compressed sensing Hyperspectral sensing Reconstruction algorithms Wavelet transforms Mathematical modeling Sensors Wavelets Imaging systems

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visualisation of Earth Deformation in 2D

Visualisation of Earth Deformation in 2D

引用

International Conference on Computational Intelligence, Communication systems and Networks, CICSYN

作者： Nor Anita Fairos bt. Ismail Sheikh Nasir Kamarudin Mohd Sharfy bin Mohd Rahim J.G. Liu P. Mason Faculty of Science & Information System Vi Cube Laboratory Johor Bahru Malaysia Department of Earth Science and Engineering Imperial College London UK

The rapidly growing field of remote sensing is beginning to supply massive quantities of high-resolution imagery of the Earth and other planets. In the earth sciences, parallel supercomputers have always played a prominent role in the visualization of this imagery, and in other image processing applications designed to enhance and display the obtained information. imageodesy is a technique for detection and measurement of feature shifts between two images based on local feature fitting algorithms such as Normalize Cross-Correlation (Crippen, 1992) and phase correlation. This technique allows the vast archives of optical imagery, collected by satellite systems such as SPOT and Landsat, to be used not only to detect but also to measure the subtle terrain displacements associated with earthquakes, glacial motion and volcanic processes, all to within sub-resolution accuracy and precision is also a major factor.

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Fast multiresolution contour completion

Fast multiresolution contour completion

引用

Conference on image processing - algorithms and systems vi

作者： Papari, G. Petkov, N. Univ Groningen Inst Math & Comp Sci NL-9700 AK Groningen Netherlands

ISBN: (纸本)9780819469847

We consider the problem of improving contour detection by filling gaps between collinear contour pieces. A fast algorithm is proposed which takes into account local edge orientation and local curvature. Each edge point is replaced by a curved elongated patch, whose orientation and curvature match the local edge orientation and edge. The proposed contour completion algorithm is integrated in a multiresolution framework for contour detection. Experimental results show the superiority of the proposed method to other well-established approaches.

关键词： Sensors Detection and tracking algorithms Binary data image analysis image processing Information visualization Logic algorithms Machine vision Mathematics

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An image restoration approach for artificial compound eyes

An image restoration approach for artificial compound eyes

引用

Conference on image processing - algorithms and systems vi

作者： Tudela, Raul Brueckner, Andreas Duparre, Jacques Braeuer, Andreas Fraunhofer Inst Appl Opt & Precis Engn D-07745 Jena Germany

ISBN: (纸本)9780819469847

Natural compound eyes combine a small eye volume with a large field of view (FOV) at the cost of comparatively low spatial resolution. Based on these principles, an artificial apposition compound-eye imaging system has been developed. In this system the total FOV is given by the number of channels along one axis multiplied with the sampling angle between channels. In order to increase the image resolution for a fixed FOV the sampling angle is made small. However, depending on the size of the acceptance angle, the FOVs of adjacent channels overlap which causes a reduction of contrast in the overall image. In this work we study the feasibility of using digital post-processing methods for images obtained with a thin compound-eye camera to overcome this reduction in contrast. We chose the Wiener filter for the post-processing and carried out simulations and experimental measurements to verify its use.

关键词： imaging systems compound-eye micro optics image processing Wiener filter

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Topological pattern recognition and reconstruction from noise-affected boundary patterns

Topological pattern recognition and reconstruction from nois...

引用

Conference on image processing - algorithms and systems vi

作者： Hu, Chialun John Univ Colorado Dept Elect & Comp Engn Boulder CO 80301 USA

ISBN: (纸本)9780819469847

Using our recently modified curve-fitting-topological-coding (CFTC) computer program, we can automatically obtain a precise topological code to represent the topological property of a closely reconstructed boundary of a selected object in an edge-detected picture. This topological property is perhaps the most important property to be used for object identification. It is very accurate, yet very robust, because the topological property is independent of geometrical location, shape, size, orientation, and viewing angles. It is very accurate if two different objects to be differentiated or to be identified have different boundary topologies. Patch noise and obscuring noise can also be automatically eliminated as shown in some live experiments.

关键词： Reconstruction algorithms Pattern recognition Analog electronics Raster graphics image processing Binary data Software Computer engineering Electronic imaging Imaging systems

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Latent fingerprint system performance modeling

Latent fingerprint system performance modeling

引用

Conference on image processing - algorithms and systems vi

作者： Dvornychenko, V. N. Natl Inst Stand & Technol Informat Technol Lab Image Grp Gaithersburg MD 20899 USA

ISBN: (纸本)9780819469847

This paper presents some analytic tools for modeling and analyzing the performance of latent fingerprint matchers. While the tools and techniques presented are not necessarily new, the manner in which these are employed is believed to be novel. It is shown that using relatively simple techniques, valuable insights are provided into what is otherwise nearly an intractable problem. In addition, three other topics are touched upon: 1) We proved a thumb-nail sketch of NIST's ELFT project. The purpose of the ELFT project is to investigate the steps required to achieve a partial lights-out latent fingerprint processing capability; 2) Preliminary data obtained from this project are analyzed using the proposed techniques; 3) An analysis is provided for predicting the performance of a "fully-populated" system when measurements can realistically only be performed on a small subset of the full-up repository/background/gallery.

关键词： systems modeling Performance modeling Data modeling Autoregressive models Analytical research image processing Biological research Computing systems Data acquisition Palladium

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Two Fibonacci P-code based image scrambling algorithms

Two Fibonacci P-code based image scrambling algorithms

引用

Conference on image processing - algorithms and systems vi

作者： Zhou, Yicong Agaian, Sos Joyner, Valencia M. Panetta, Karen Tufts Univ Dept Elect & Comp Engn Medford MA 02155 USA Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA

ISBN: (纸本)9780819469847

image scrambling is used to make images visually unrecognizable such that unauthorized users have difficulty decoding the scrambled image to access the original image. This article presents two new image scrambling algorithms based on Fibonacci p-code, a parametric sequence. The first algorithm works in spatial domain and the second in frequency domain (including JPEG domain). A parameter, p, is used as a security-key and has many possible choices to guarantee the high security of the scrambled images. The presented algorithms can be implemented for encoding/decoding both in full and partial image scrambling, and can be used in real-time applications, such as image data hiding and encryption. Examples of image scrambling are provided. Computer simulations are shown to demonstrate that the presented methods also have good performance in common image attacks such as cutting (data loss), compression and noise. The new scrambling methods can be implemented on grey level images and 3-color components in color images. A new Lucas p-code is also introduced. The scrambling images based on Fibonacci p-code are also compared to the scrambling results of classic Fibonacci number and Lucas p-code. This will demonstrate that the classical Fibonacci number is a special sequence of Fibonacci p-code and show the different scrambling results of Fibonacci p-code and Lucas p-code.

关键词： image scrambling Fibonacci p-code Lucas p-code

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An efficient detection technique for removing random-valued impulse noise in images

An efficient detection technique for removing random-valued ...

引用

Conference on image processing - algorithms and systems vi

作者： Awad, Ali S. Man, Hong Stevens Inst Technol Hoboken NJ 07030 USA

ISBN: (纸本)9780819469847

In this paper we propose a new technique to detect random-valued impulse noise in images. In this method, the noisy pixels are detected iteratively through several phases. In each phase, a pixel will be marked as a noisy pixel if it does not have sufficient number of similar pixels inside the neighborhood window. The size of the window increases over the phases, so does the sufficient similar neighbor criterion. After the detection phases, all noisy pixels will be corrected in a recovering process. We compare the performance of this method with other recently published methods, in terms of peak signal to noise ratio and perceptual quality of the restored images. From the simulation results we observe that this method outperforms all other methods at medium to high noise rates. The algorithm is very fast, providing consistent performance over a wide range of noise rates. It also preserves fine details of the image.

关键词： image denoising noise detection noise removal image enhancement image recovery

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Uncertainty analysis of an evolutionary algorithm to develop remote sensing spectral indices

Uncertainty analysis of an evolutionary algorithm to develop...

引用

Conference on image processing - algorithms and systems vi

作者： Momm, H. G. Easson, Greg Kuszmaul, Joel Univ Mississippi Dept Geol & Geol Engn University MS 38677 USA

ISBN: (纸本)9780819469847

The need for information extracted from remotely sensed data has increased in recent decades. To address this issue, research is being conducted to develop a complete multi-stage supervised object recognition system. The first stage of this system couples genetic programming with standard unsupervised clustering algorithms to search for the optimal preprocessing function. This manuscript addresses the quantification and the characterization of the uncertainty involved in the random creation of the first set of candidate solutions from which the algorithm begins. We used a Monte Carlo type simulation involving 800 independent realizations and then analyzed the distribution of the final results. Two independent convergence approaches were investigated: [1] convergence based solely on genetic operations (standard) and [2] convergence based on genetic operations with subsequent insertion of new genetic material (restarting). Results indicate that the introduction of new genetic material should be incorporated into the preprocessing framework to enhance convergence and to reduce variability.

关键词： genetic programming uncertainty image classification remote sensing

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Identification and ranking of relevant image content

Identification and ranking of relevant image content

引用

Conference on image processing - algorithms and systems vi

作者： Jaber, Mustafa Saber, Eli Dianat, Sohail Shaw, Mark Bhaskar, Ranjit Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Rochester NY 14623 USA Rochester Inst Technol Dept Elect Engn Rochester NY 14623 USA Hewlett Packard Corp Color & Imaging Boise ID 83714 USA

ISBN: (纸本)9780819469847

In this paper, we present an image understanding algorithm for automatically identifying and ranking different image regions into several levels of importance. Given a color image, specialized maps for classifying image content namely: weighted similarity, weighted homogeneity, image contrast and memory colors are generated and combined to provide a metric for perceptual importance classification. Further analysis yields a region ranking map which sorts the image content into different levels of significance. The algorithm was tested on a large database of color images that consists of the Berkeley segmentation dataset as well as many other internal images. Experimental results show that our technique matches human manual ranking with 90% efficiency. Applications of the proposed algorithm include image rendering, classification, indexing and retrieval.

关键词： image understanding region ranking importance map region of interest

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