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检索条件"机构=Electrical and Computer Engineering Department Remote Sensing and Image Processing Laboratory"

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Automated generation of an efficient MPEG-4 Reconfigurable Video Coding decoder implementation

Automated generation of an efficient MPEG-4 Reconfigurable V...

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Conference on Design and Architectures for Signal and image processing

作者： Ruirui Gu Jonathan Piat Mickael Raulet Jorn W. Janneck Shuvra S. Bhattacharyya Department of Electrical and Computer Engineering University of Maryland College Park MD USA IETR Laboratory UMR CNRS 6164 Image and Remote Sensing Group Rennes France

This paper proposes an automatic design flow from user-friendly design to efficient implementation of video processing systems. This design flow starts with the use of coarse-grain dataflow representations based on the CAL language, which is a complete language for dataflow programming of embedded systems. Our approach integrates previously developed techniques for detecting synchronous dataflow (SDF) regions within larger CAL networks, and exploiting the static structure of such regions using analysis tools in The Dataflow interchange format Package (TDP). Using a new XML format that we have developed to exchange dataflow information between different dataflow tools, we explore systematic implementation of signal processing systems using CAL, SDF-like region detection, TDP-based static scheduling, and CAL-to-C (CAL2C) translation. Our approach, which is a novel integration of three complementary dataflow tools - the CAL parser, TDP, and CAL2C - is demonstrated on an MPEG Reconfigurable Video Coding (RVC) decoder.

关键词： Transform coding XML Video coding Decoding Digital signal processing Computational modeling Libraries

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Motion Compensated Frame Interpolation Using Adaptive Adjacency Pixel Information

Motion Compensated Frame Interpolation Using Adaptive Adjace...

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International Conference on computer Graphics, Imaging and Visualization, CGIV

作者： Hyeongchul Oh Joohyun Lee Changki Min Jechang Jeong Image Communication and Signal Processing Laboratory Department of Electrical and Computer Engineering Hanyang University Seoul South Korea

We propose an adaptive motion compensated frame interpolation scheme which is capable of developing a frame rate from a lower number into a higher number and a decoded video quality at the decoder. The proposed algorithm utilizes the preliminary frames of the forward and backward directions using bilateral prediction. In the processing of the preliminary frames, an additional interpolation is performed to fill the occlusion areas. If the calculated values between the reference and current frames are larger than the predetermined threshold, the block is chosen as the occlusion area. In addition, we performed a re-search in order to acquire the best blocks, taking into account the number of available adjacent blocks for the occlusion areas. The experimental results show that the performance of the proposed algorithm has better PSNR and visual quality than those of the conventional methods.

关键词： Interpolation Pixel Robustness PSNR Motion estimation Algorithm design and analysis Motion compensation

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Gender estimation based on physiological features of the face

Gender estimation based on physiological features of the fac...

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International Symposium on Signal processing and Its Applications (ISSPA)

作者： C.H. Ting U.U. Sheikh S.A.R Abu-Bakar Computer Vision Video and Image Processing Research Laboratory Department of Microelectronics and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

In this paper, we present a gender estimation technique that will determine whether a person looking at the camera is a male or female. Several facial features extracted from a face are passed to post-image-processing operations before they are sent to a rule-base classifier. We applied our technique to both static passport-like photos as well as several video sequences consisting of a single face each. Our database also contains images of females wearing headscarf as well as bald men. Our initial results showed a very promising outcome. For static face images, we obtained an accuracy of 100% correct gender estimation for females and 98% for males while for video sequences, the accuracy obtained was 87.5% for females and 70% for males.

关键词： Face Hair image resolution Estimation computers Accuracy

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Improved learning in grid-to-grid neural network via clustering

Improved learning in grid-to-grid neural network via cluster...

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International Joint Conference on Neural Networks (IJCNN)

作者： W. White K. Iftekharuddin A. Bouzerdoum Intelligent Systems and Image Processing Laboratory Department of Electrical and Computer Engineering University of Memphis TN USA Department of Electrical and Computer Engineering University of Memphis TN USA School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong NSW Australia

The maze traversal problem involves finding the shortest distance to the goal from any position in a maze. Such maze solving problems have been an interesting challenge in computational intelligence. Previous work has shown that grid-to-grid neural networks such as the cellular simultaneous recurrent neural network (CSRN) can effectively solve simple maze traversing problems better than other iterative algorithms such as the feedforward multi layer perceptron (MLP). In this work, we investigate improved learning for the CSRN maze solving problem by exploiting relevant information about the maze. We cluster parts of the maze using relevant state information and show an improvement in learning performance. We also study the effect of the number of clusters on the learning rate for the maze solving problem. Furthermore, we investigate a few code optimization techniques to improve the run time efficiency. The outcome of this research may have direct implication in rapid search and recovery, disaster planning and autonomous navigation among others.

关键词： Euclidean distance Kalman filters Training Navigation Artificial neural networks Testing

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A LOW COMPLEXITY METHOD FOR DETECTION OF TEXT AREA IN NATURAL imageS

A LOW COMPLEXITY METHOD FOR DETECTION OF TEXT AREA IN NATURA...

引用

IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Katherine L. Bouman Golnaz Abdollahian Mireille Boutin Edward J. Delp Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI 48109 USA Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette Indiana USA

ISBN: (纸本)9781424442959

We propose a low complexity method for segmentation of text regions in natural images. This algorithm is designed for mobile applications (e.g. unmanned or hand-held devices) in which computational and energy resources are limited. No prior assumption is made regarding the text size, font, language, character set or the camera angle. However, the text is assumed to be located on a piecewise homogeneous background with a contrasting color. We have deployed our method on a Nokia N800 Internet tablet as part of a system for automatic detection and translation of outdoor signs. Our experiments show that the 0.3 megapixel images taken by the phone camera can be accurately segmented within the device in a fraction of a second.

关键词： Text Detection Text Segmentation Sign Detection Mobile Devices Mobile devices text segmentation images lens angle hand-held equipment Mobile Applications UNMANNED automatic detection Energy sources

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Bacterial Foraging Algorithm for neutron radiography image quality improvement

Bacterial Foraging Algorithm for neutron radiography image q...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： S. Saadi A. Kouzou A. Guessoum M. Bettayeb University Ziane Achour of Djelfa Algeria Department of Electronics Signal and image Processing Laboratory USDB Burgas Algeria Department of Electrical and Computer Engineering University of Sharjah UAE

We want to implement a new optimal approach for image restoration problem, which is useful for neutron radiography images enhancement to assist the physician interpreter on his evaluation. Our approach is based on using swarm intelligence optimization algorithms to solve a least squares minimization ill-posed problem, using Bacterial Foraging Optimization (BFO) Algorithm. To get smoothed images in presence of noise, a Laplacian constraint is introduced for regularization purpose.

关键词： Wiener filter image restoration Radiography Strontium

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Improved hurricane active/passive simulated wind vector retrievals

Improved hurricane active/passive simulated wind vector retr...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Suleiman Alsweiss Peth Laupattarakasem Salem El-Nimri W. Linwood Jones Svetla Hristova-Veleva Central Florida Remote Sensing Laboratory Department of Electrical Engineering & Computer Science University of Central Florida Orlando FL USA Jet Propulsion Laboratory Pasadena CA USA

Microwave scatterometers are the standard for satellite ocean vector winds (OVW) measurements, and they provide the major source of global ocean surface winds observations for scientific and operational applications. A major challenge for Ku-band scatterometry missions is to provide reliable retrievals in the presence of precipitation, particularly in extreme ocean wind events that are usually associated with intense rain. This paper explores the advantages of combining dual frequency (C- and Ku-band) scatterometer measurements and passive microwave observations to improve high wind speed retrievals. For this study, a conceptual design proposed by the Jet Propulsion laboratory for a Dual Frequency Scatterometer (DFS) to fly onboard the future Japan Aerospace Exploration Agency (JAXA) GCOM-W2 mission with the Advanced Microwave Scanning Radiometer (AMSR) was adopted. A computer simulation that combines the DFS and AMSR measurements was used to develop an artificial neural network OVW retrieval algorithm. The Weather Research and Forecasting (WRF) numerical weather model of Hurricane Katrina (2005) was used as the nature run (surface truth), and simulated OVW retrievals demonstrate that this new technique offers a robust option to extend the useful wind speed measurements range beyond the current operating scatterometers for future satellite missions.

关键词： Radar measurements Rain Wind speed Sea measurements Microwave measurements Hurricanes

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A comparative study to select an image deconvolution method

A comparative study to select an image deconvolution method

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： S. Saadi A. Kouzou A. Guessoum M. Bettayeb Department of Electronics University Ziane Achour of Djelfa Algeria Department of Electronics Signal and Image Processing Laboratory USDB Burgas Algeria Department of Electrical and Computer Engineering University of Sharjah UAE

image deconvolution is an important subject in image processing. It is an ill-posed inverse problem, so regularization techniques are used to solve this problem by adding constraints to the objective function. Various popular algorithms have been developed to solve such problem. This paper studies various approaches to the nonlinear degraded images restoration problem which are useful in many images enhancement applications. Swarm intelligence is applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method which is often used. In this work, we attempt to reconstruct or recover corrupted images that have been degraded during acquisition; using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition (TSVD) method is also considered for image deconvolution in this paper. A comparison between these methods made on examples is included.

关键词： Noise measurement

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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International Conference on Intelligent and Advanced Systems, ICIAS

作者： Mahdi Ramezani Amin Heidari Emad Fatemizadeh Hamid Soltanian-Zadeh Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearest-neighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Clustering algorithms Algorithm design and analysis Correlation Approximation methods Independent component analysis Time series analysis Approximation algorithms

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Enhancing the interpretability of genetic fuzzy classifiers in land cover classification from hyperspectral satellite imagery

Enhancing the interpretability of genetic fuzzy classifiers ...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Dimitris G. Stavrakoudis Georgia N. Galidaki Ioannis Z. Gitas John B. Theocharis Department of Electrical and Computer Engineering Division of Electronics Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Laboratory of Forest Management and Remote Sensing School of Forestry and Natural Environment Aristotle University of Thessaloniki Thessaloniki Greece

A Feature Selective Linguistic Classifier (FeSLiC) is proposed in this paper, for land cover classification from hyperspectral images. FeSLiC is a Genetic Fuzzy Rule-Based Classification System (GFRBCS), designed under the Iterative Rule Learning (IRL) approach. A local feature selection scheme is employed, designed to guide the genetic evolution, through the evaluation of deterministic information about the relevancy of each feature with respect to its classification ability. A simplification post-processing stage significantly enhances the interpretability of the derived model, by reducing its structure size. The performance of the classifier is finally optimized through a genetic tuning stage. Comparative results using an Earth Observing-1 (EO-1) Hyperion satellite image indicate the effectiveness of the proposed methodology in handling high-dimensional feature spaces.

关键词： Classification algorithms Training Input variables Genetics Biological cells Pragmatics Pattern matching

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