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检索条件"任意字段=Wavelets: Applications in Signal and Image Processing X"

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Development and characterization of a 300mm dual-side alignment stepper

Development and characterization of a 300mm dual-side alignm...

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Conference on Optical Microlithography xx

作者： Flack, Warren W. True, Emily M. Hsieh, Robert Fuchs, Detlef Ellis, Ray Ultratech Inc San Jose CA 95134 USA

ISBN: (纸本)9780819466396

A number of new packaging technologies are driving the demand for high performance dual-side alignment (DSA) on 300 mm lithography systems. Advanced system in package (SiP) techniques will require through silicon vias to allow very high density vertical interchip wiring of multiple device stacks. These through silicon vias need to be freely placed in the device which creates a requirement for tight registration of the back-to-front side alignment. In the MEMS area, wafer level packaging is being used for applications where the device must interact with the outside environment without performance restrictions from the packaging. An example is image sensor chips where the charge-coupled device is on the front side and the electrical interconnects to the signal processing die are on the back side. This application requires dual-side alignment on a 300 mm bonded silicon glass sandwich structure. To support these packaging applications a new lithography stepper capable of dual-side alignment on 300 mm wafers has been developed. This stepper employs an innovative and flexible system for back-to-front side alignment to support a wide range of packaging applications. This paper discusses the design and integration of the alignment system on a broad band, low numerical aperture stepper. Experimental target capture for CMOS image sensor applications is shown. Dual-side overlay performance data on multiple wafers and lots is reviewed.

关键词： dual-side alignment back-to-front alignment system in package wafer level packaging MEMS image sensors 300mm wafers lithography tool performance

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Nanocrystal clusters in combination with spectral imaging to improve sensitivity in antibody labeling applications of fluorescent nanocrystals

Nanocrystal clusters in combination with spectral imaging to...

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Conference on Colloidal Quantum Dots for Biomedical applications II

作者： Maier, John S. Panza, Janice L. Bootman, Matt ChemImage Corp 7301 Penn Ave Pittsburgh PA 15208 USA Crystalplex Pittsburgh PA 15238 USA

ISBN: (纸本)9780819465610

Composition- tunable nanocrystals are fluorescent nanoparticles with a uniform particle size and with adjustable optical characteristics. When used for optical labeling of biomolecular targets these and other nanotechnology solutions have enabled new approaches which are possible because of the high optical output, narrow spectral signal, consistent quantum efficiency across a broad emission range and long lived fluorescent behavior of the nanocrystals. When coupled with spectral imaging the full potential of multiplexing multiple probes in a complex matrix can be realized. Spectral imaging can be used to improve sensitivity of narrowband fluorophores through application of chemometric image processing techniques used to reduce the influence of autofluorescence background. Composition- tunable nanocrystals can be complexed together to form nanoclusters which have the advantage of significantly stronger signal and therefore a higher sensitivity. These nanoclusters can be targeted in biomolecular systems using standard live-cell labeling and immunohistochemistry based techniques. Composition-tunable nanocrystals and nanoclusters have comparable mass and brightness across a wide emission range. This enables the production of nanocrystal-based probes that have comparable reactivity and sensitivity over a large color range. We present spectral imaging results of antibody targeted nanocrystal cluster labeling of target proteins in cultured cells and a Western blot experiment. The combination of spectral imaging with the use of clusters of nanocrystals further improves the sensitivity over either of the approaches independently.

关键词： nanocrystals quantum dot spectral imaging

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Spread transform capacities for image media using complex wavelets

Spread transform capacities for image media using complex wa...

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International Symposium on signal processing and Its applications (ISSPA)

作者： A. I. Thompson A. Bouridane F. Kurugollu School of Electronics Electrical Engineering and Computer Science Queen's University Belfast UK

As the area of data hiding has matured information theoretic methods of calculating the capacity of data hiding schemes have arisen. This paper uses a dual tree wavelet transform and non redundant complex wavelet transform along with a spread transform data hiding algorithm to obtain improved levels of data hiding capacity. The information theoretic model used involves the use of game theory applied to optimize the embedding and attack strategy across parallel Gaussian channels. Capacity results are compared with those recently published by Ghouti et al.

关键词： Wavelet transforms Discrete wavelet transforms Data encapsulation Gaussian channels Spread spectrum communication Quantization Wavelet coefficients Wavelet domain Filters Computer science

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Model based compression of the calibration matrix for hyperspectral imaging systems

Model based compression of the calibration matrix for hypers...

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Conference on Mathematics of Data/image Pattern Recongnition, Compression, Coding, and Encryption x, with applications

作者： Scholl, James F. Hege, E. Keith O'Connell, Daniel Dereniak, Eustace L. Univ Arizona Coll Opt Sci 1630 E Univ Blvd Tucson AZ 85721 USA MKS Imaging Technol LLC Tucson AZ 85718 USA Univ Arizona Dept Astron Steward Observ Tucson AZ 85721 USA Hun Photon Wailuku HI 96793 USA

ISBN: (纸本)9780819468482

In hyperspectral imaging systems with a continuous-to-discrete (CD) model, the goal is to solve the matrix equation g = H theta + n for theta. Here g is a data vector obtained on pixels on a focal plane array (FPA), and n is the additive pixel noise vector. The hyperspectral object cube f(x, y, lambda) to be recovered is represented by theta, which is the vectorized set of expansion coefficients of f with respect to a family of functions. The imaging operator is the system matrix H of which its columns represent the projection of each expansion function onto the FPA. Hence an estimate of the object cube f(x, y, lambda) is reconstructed from these recovered expansion function projection coefficients. Furthermore H is equivalently a calibration matrix, and amenable to an analytic description. Since the number of expansion functions is large, and the number of pixels on an FPA is large, H becomes huge and very unwieldy to store. We describe a means by which we can reduce the effective size of H by taking advantage of the analytic model of the imaging system and converting H into a series of look-up tables. By this method we have been able to drastically reduce the storage requirements for H from terabytes to sub-megabyte sizes. We provide an example of this technique in isoplanatic and polychromatic calibration of a flash hyperspectral imaging system. These sets of lookup tables are expansion function independent and also independent of object cube sampling.

关键词： diffraction theory hyperspectral signal processing remote sensing

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Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

Information theoretic partitioning and confidence based weig...

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Conference on signal processing, Sensor Fusion, and Target Recognition xVI

作者： Prasad, S. Bruce, L. M. Mississippi State Univ Dept Elect & Comp Engn Mississippi State MS 39759 USA

ISBN: (纸本)9780819466891

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognit

关键词： multi-classifiers information fusion automatic target recognition mutual information confidence measure

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Detection and identification of human targets in radar data

Detection and identification of human targets in radar data

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Conference on signal processing, Sensor Fusion, and Target Recognition xVI

作者： Guerbuez, Sevgi Z. Melvin, William L. Williams, Douglas B. Georgia Inst Technol Ctr Signal & Image Proc Sch Elect & Comp Engn Atlanta GA 30332 USA Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9780819466891

Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

关键词： human detection personnel detection target identification

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Change detection in urban scenes by fusion of SAR and hyperspectral data

Change detection in urban scenes by fusion of SAR and hypers...

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Conference on Remote Sensing for Environmental Monitoring, GIS applications, and Geol VIIl

作者： Borghys, Dirk Shimoni, Michal Perneel, Christlaan Royal Mil Acad Signal & Image Ctr Renaissancelaan 30 B-1000 Brussels Belgium Royal Mil Acad Dept Math Appl Renaissancelaan 30 B-1000 Brussels Belgium

ISBN: (纸本)9780819469076

Urban areas are rapidly changing all over the world and therefore provoke the necessity to update urban maps frequently. Remote sensing has been used for many years to monitor these changes. The urban scene is characterized by a very high complexity, containing objects formed from different types of man-made materials as well as natural vegetation. Hyperspectral sensors provide the capability to map the surface materials present in the scene using their spectra and therefore to identify the main object classes in the scene in a relatively easy manner. However ambiguities persist where different types of objects are constructed of the same material. This is for instance the case for roads and roof covers. Although higher-level image processing (e.g. spatial reasoning) might be able to relief some of these constraints, this task is far from straight forward. In the current paper the authors fused information gathered using a hyperspectral sensor with that of high-resolution polarimetric SAR data. SAR data give information about the type of scattering backscatter from an object in the scene, its geometry and its dielectric properties. Therefore, the information obtained using the SAR processing is complementary to that obtained using hyperspectral data. This research was applied on a dataset consisting of hyperspectral data from the HyMAP sensor (126 channels in VIS-SWIR) and E-SAR data which consists of full-polarimetric L-band and dual-polarisation (HH and VV) x-band data. Two supervised classifications are used;'Logistic Regression' (LR) which applied to the SAR and the PoISAR data and a 'Matched Filter' which is applied to the hyperspectral data. The results of the classification are fused in order to improve the mapping of the main classes in the scene and were compared to a ground truth map that was constructed by combining a digital topographic map and a vectorized cadastral map of the research area. An adequate change detection of man-made objects in urban scen

关键词： change detection hyperspectral SAR PoISAR logistic regression urban mapping

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Empiricalanalysis of LIBS images for ovarian cancer detection

Empiricalanalysis of LIBS images for ovarian cancer detectio...

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8th International Workshop on image Analysis for Multimedia Interactive Services, WIAMIS 2007

作者： Tameze, Claude Vincelette, Robert Melikechi, Noureddine Zeljkovic, Vesna Izquierdo, Ebroul Department of Physics and Pre-Engineering Center for Research and Education in Optical Sciences and Applications Delaware State University 1200 N Dupont Highway Dover DE 19901 United States Electronic Engineering Department Queen Mary University of London London E1 4NS United Kingdom

ISBN: (纸本)076952818X

To develop a way to detect early epithelial ovarian cancer we expose blood samples to a laser. Using Laser induced breakdown spectroscopy, (LIBS) plasma images of the blood samples are generated and analyzed. In this paper we compare the images from blood specimens of cancer free mice to those of transgenic mice;that is, mice that are currently developing epithelial ovarian cancer and are approximately the same age as the disease free mice. Our ultimate goal is to look for changes in the shape and edges of the image that might indicate the presence of cancer. To analyze the images we use a nonlinear diffusion filter for enhancement of relevant image edges and removal of noise and irrelevant texture. © 2007 IEEE.

关键词： Blood

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Personal video coding for very low bit rate applications

Personal video coding for very low bit rate applications

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8th International Workshop on image Analysis for Multimedia Interactive Services, WIAMIS 2007

作者： Guaragnella, Cataldo DEE - Electrics and Electronics Department Politecnico di Bari Via E. Orabona 4 70125-Bari Italy

ISBN: (纸本)076952818X

In personal video communications, the postures assumed by the speaker during the connection are very similar. In past works the possible exploitation of inherent voice and video correlation has been proposed for the generation of a likely animation of a speaker, driven by audio information only. In this paper, a novel video coding technique is presented, based on the decomposition of the sequence spanned hyperspace in orthogonal components. Good quality video can be reconstructed at the receiver, particularly for verylow bit rate applications, with low residual error and smooth appearance both in motion reconstruction and in the complete absence of crisp coding artifacts such as blocking structures, basing on a few proper selected examples of the speaker and a multidimensional interpolation algorithm. Principal Component Analysis exploited by Singular Value Decomposition has been used to decompose the video sequence into eigen-images. A limited set of eigen-images is chosen to span the whole video sequence subspace. Only coefficients to be used in the interpolation procedure are transmitted along the communication channel. Preliminary results are presented for Akyio QCJF video sequence. © 2007 IEEE.

关键词： Singular value decomposition

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Multi-dimensional spline-based non-rigid image registration

Multi-dimensional spline-based non-rigid image registration

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Medical Imaging 2007 Conference

作者： Viola, Francesco Guenther, Drake A. Coe, Ryan L. Walker, William F. Univ Virginia Dept Biomed Engn 415 Lane Rd Charlottesville VA 22908 USA Univ Virginia Dept Elect & Comp Engn Charlottesville VA 22904 USA

ISBN: (纸本)9780819466310

image registration, or equivalently motion estimation, plays a central role in a broad range of ultrasound applications including elastography, estimation of blood or tissue motion, radiation force imaging, and extended field of view imaging. Because of its central significance, motion estimation accuracy, precision, and computational cost are of critical importance. Furthermore, since motion estimation is typically performed on sampled signals, while estimates are usually desired over a continuous domain, performance should be considered in conjunction with associated interpolation. We have previously presented a highly accurate, spline-based time delay estimator that directly determines sub-sample time delay estimates from sampled data. The algorithm uses cubic splines to produce a continuous time representation of a reference signal and then computes an analytical matching function between this reference and a delayed signal. The location of the minima of this ftinction yields estimates of the time delay. In this paper we describe a MUlti-dimensional Spline-based Estimator (MUSE) that allows accurate and precise estimation of multi-dimensional displacements/strain components from multi-dimensional data sets. In this paper we describe the mathematical formulation for three-dimensional (313) motion/strain estimation and present simulation results to assess the intrinsic bias and standard deviation of this algorithm and compare it to currently available multi-dimensional estimators. In 1,000 noise-free simulations we found that 2D MUSE exhibits maximum bias errors of 4.8nm and 297nm in range and azimuth respectively. The maximum simulated standard deviation of estimates in both dimensions was comparable at 0.0026 samples (corresponding to 54nm axially and 378nm laterally). These results are two to three orders of magnitude lower than currently used 2D tracking methods. Simulation of performance in 3D yielded similar results to those observed in 2D. We also performed

关键词： ultrasound motion estimation image registration strain estimation elasticity imaging splines

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