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conference on applications of Digital Image processing XXV

作者： Timchenko, LI Kutaev, YF Kozhemyako, VP Yarovyy, AA Gertsiy, AA Terenchuk, AT Shweiki, N Vinnytsia State Tech Univ Dept Designing Comp Telecommun & Biomed Devices UA-21021 Vinnytsia Ukraine

ISBN: (纸本)0819445576

Authors have worked out a nonstationary signal analysis method on an example of research of laser lines. This method disclosed relationship between signal approximation coefficients and geometry signal characterizations (for instance, energy center, moment of inertia). An example, which is demonstrating an application of this method for exact coordinate determination problem in laser line at displacement compensation in laser imaging are present.

关键词： parallel-hierarchical network laser path real-time image sequences dynamic tunnelling system fractal

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Edge-preserved neural network model for image restoration

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JOURNAL OF ELECTRONIC imaging 2001年第3期10卷 735-743页

作者： Bao, P Wang, DH Hong Kong Polytech Univ Dept Comp Kowloon Hong Kong Peoples R China

This paper presents a combined approach for image restoration with edge-preserving regularization, subband coding, and artificial neural network. The edge information is detected from the source image as a priori knowledge to recover the details and reduce the ringing artifact of the subband coded image. The multilayer perceptron model is employed to implement the restoration of images. The main merit of the presented approach is that the neural network model is massively parallel with stronger robustness for transmission noise and parameter or structure perturbation, and it can be realized by very large scale integrated technologies for realtime applications. To evaluate the performance of the proposed approach, a comparative study with the set partitioning in hierarchical tree (SPIHT) has been made by using a set of gray-scale digital images. The experiment has shown that the proposed approach could result in considerably better performances compared with SPIHT on both objective and subjective quality for lower compression ratio subband coded image. (C) 2001 SPIE and IS&T.

关键词： Neural networks Image restoration Image compression Image quality Computer programming Chromium Network architectures Image processing Neurons Quantization

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Three-dimensional region-based adaptive image processing techniques for volume visualization applications

Three-dimensional region-based adaptive image processing tec...

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conference on Image Display

作者： deDeusLopes, R Zuffo, MK Rangayyan, RM UNIV SAO PAULO ESCOLA POLITECNLAB SISTEMAS INTEGRAVEISBR-05508900 SAO PAULOBRAZIL

ISBN: (纸本)0819420824

Recent advances in three-dimensional (3D) imaging techniques have expanded the scope of applications of volume visualization to many areas such as medical imaging, scientific visualization, robotic vision, and virtual reality. Advanced image filtering, enhancement, and analysis techniques are being developed in parallel in the field of digital image processing. Although the fields cited have many aspects in common, it appears that many of the latest developments in image processing are not being applied to the fullest extent possible in visualization. It is common to encounter the use of rather simple and elementary image pre- processing operations being used in visualization and 3D imaging applications. The purpose of this paper is to present an overview of selected topics from recent developments in adaptive image processing and demonstrate or suggest their applications in volume visualization. The techniques include adaptive noise removal; improvement of contrast and visibility of objects; space-variant deblurring and restoration; segmentation-based lossless coding for data compression; and perception-based measures for analysis, enhancement, and rendering. The techniques share the common base of identification of adaptive regions by region growing, which lends them a perceptual basis related to the human visual system. Preliminary results obtained with some of the techniques implemented so far are used to illustrate the concepts involved, and to indicate potential performance capabilities of the methods.

关键词： volume visualization medical imaging three-dimensional image processing image enhancement image coding image compression adaptive image processing region-based image processing noise removal contrast enhancement

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An Easy Setup for parallel Medical Image processing: Using Taverna and ARC

An Easy Setup for Parallel Medical Image Processing: Using T...

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7th Healthgrid conference

作者： Zhou, Xin Krabbenhoeft, Hajo Niinimaeki, Marko Depeursinge, Adrien Moller, Steffen Mueller, Henning Univ Hosp Geneva Med Informat 24 Rue Micheli du Crest Geneva Switzerland Univ Geneva Geneva Switzerland Univ Lubeck Inst Neuro & Bioinformat Lubeck Germany Univ Appl Sci Western Switzerland Business Informat Syst Sierre Switzerland

ISBN: (纸本)9781607500278

Medical image processing is known as a computationally expensive and data intensive domain. It is thus well suited for Grid computing However, Grid computing usually requires the applications to be designed for parallel processing, which is a challenge for medical imaging researches in hospitals that are most often not used to this Making parallel programming methods easier to apply can promote Grid technologies in clinical environments. Readily available, functional tools with an intuitive interface are required to really promote healthgrids Moreover, the tools need to be well integrated with the Grid infrastructure. To facilitate the adoption of Gilds in the Geneva University Hospitals we have set up a develop environment based on the Taverna workflow engine Its usage with a medical imaging application on the hospitals' internal Grid cluster is presented in this paper.

关键词： Grid networks Taverna medical imaging research image processing ARC

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Commodity cluster and hardware-based massively parallel implementations of hyperspectral imaging algorithms

Commodity cluster and hardware-based massively parallel impl...

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conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII

作者： Plaza, Antonio Chang, Chein-, I Plaza, Javier Valencia, David Univ Extremadura Comp Sci Dept Avda Univ S-N E-10071 Caceres Spain Univ Maryland Dept Comp Sci & Elect Engn Remote Sensing Signal & Image Proc Lab Baltimore MD 21250 USA

ISBN: (纸本)0819462896

The incorporation of hyperspectral sensors aboard airborne/satellite platforms is currently producing a nearly continual stream of multidimensional image data, and this high data volume has soon introduced new processing challenges. The price paid for the wealth spatial and spectral information available from hyperspectral sensors is the enormous amounts of data that they generate. Several applications exist, however, where having the desired information calculated quickly enough for practical use is highly desirable. High computing performance of algorithm analysis is particularly important in homeland defense and security applications, in which swift decisions often involve detection of (sub-pixel) military targets (including hostile weaponry, camouflage, concealment, and decoys) or chemical/biological agents. In order to speed-up computational performance of hyperspectral imaging algorithms, this paper develops several fast parallel data processing techniques. Techniques include four classes of algorithms: (1) unsupervised classification, (2) spectral unmixing, and (3) automatic target recognition, and (4) onboard data compression. A massively parallel Beowulf cluster (Thunderhead) at NASA's Goddard Space Flight Center in Maryland is used to measure parallel performance of the proposed algorithms. In order to explore the viability of developing onboard, real-time hyperspectral data compression algorithms, a Xilinx Virtex-II field programmable gate array (FPGA) is also used in experiments. Our quantitative and comparative assessment of parallel techniques and strategies may help image analysts in selection of parallel hyperspectral algorithms for specific applications.

关键词： hyperspectral imaging parallel computing commodity clusters field programmable gate arrays

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Polarimetric imaging mobile phone application for large-area surface inspection 27

Polarimetric imaging mobile phone application for large-area...

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conference on Novel Optical Systems, Methods, and applications XXVII

作者： Martini, Carlo Hahlweg, Cornelius F. Bbw Hsch Wagner Regeny Str 21 D-12489 Berlin Germany

ISBN: (纸本)9781510679207;9781510679214

This paper is intended as a short follow-up to our last publication on the use of polarization-based imaging techniques and metrology applications. With their increasing resolution, memory availability and computing capacity, smartphones have become a common means for image and video documentation, geodetic and metrological data acquisition and similar applications in recent years. We are investigating concepts for smartphone-based polarimetric image acquisition and evaluation in field measurement campaigns. Technical applications are, for example, the mobile examination of larger areas with regard to contamination, damage to coatings, corrosion and the like, but also artistic photography, e.g. for paintings and sculptures. In addition to pure data acquisition, image pre-processing and analysis can be carried out in the field by means of mobile image processing applications. In the paper we discuss such concepts, their feasibility and robust extensions for smartphones that could lead to applications that actually take advantage of the smartphone's mobility.

关键词： polarization imaging mobile device surface inspection contamination detection dielectric layers cross- and parallel polarization

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Real-time weighted pose-space deformation on the GPU

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COMPUTER GRAPHICS FORUM 2006年第3期25卷 439-448页

作者： Rhee, Taehyun Lewis, J. P. Neumann, Ulrich Univ So Calif Los Angeles CA USA Stanford Univ Stanford CA 94305 USA

WPSD (Weighted Pose Space Deformation) is an example based skinning method for articulated body animation. The per-vertex computation required in WPSD can be parallelized in a SIMD (Single Instruction Multiple Data) manner and implemented on a GPU. While such vertex-parallel computation is often done on the GPU vertex processors, further parallelism can potentially be obtained by using the fragment processors. In this paper, we develop a parallel deformation method using the GPU fragment processors. Joint weights for each vertex are automatically calculated from sample poses, thereby reducing manual effort and enhancing the quality of WPSD as well as SSD (Skeletal Subspace Deformation). We show sufficient speed-up of SSD, PSD (Pose Space Deformation) and WPSD to make them suitable for real-time applications.

关键词： COMPUTER graphics DIGITAL image processing GEOMETRY COMPUTER-generated imagery THREE-dimensional imaging

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Architecture and applications of wireless smart cameras (networks)

Architecture and applications of wireless smart cameras (net...

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32nd IEEE International conference on Acoustics, Speech and Signal processing

作者： Kleihorst, Richard Schueler, Ben Danilin, Alexander NXP Semicond Res High Tech Campus Eindhoven Netherlands

ISBN: (纸本)1424407281

A network of (wireless smart) cameras can analyse the scene from different views. Wireless smart cameras challenge the hardware for low-power consumption and high imaging performance. In this paper we introduce a wireless smart camera based on an SIMD video-analysis processor and an 8051 microcontroller as a local host. Wireless communication is through the IEEE802.15.4 standard. The camera constructed in this paper is to enable application research into distributed smart camera systems.

关键词： real-time vision smart camera parallel processing

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A parallel impulse-noise detection algorithm based on ensemble learning for switching median filters

A parallel impulse-noise detection algorithm based on ensemb...

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conference on parallel processing for imaging applications

作者： Duan, Fei Zhang, Yu-Jin Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9780819484093

In this paper, a highly effective and efficient ensemble learning based parallel impulse noise detection algorithm is proposed. The contribution of this paper is three-fold. First, we propose a novel intensity homogeneity metric-Directional Homogeneity Descriptor(DHD), which has very powerful discriminative ability and has been proven in our previous work. 1 Second, this proposed algorithm has high parallelism in feature extraction stage, classifier training, and testing stage. And the proposed architecture are very suitable for distributed processing. Finally, instead of manually tune the thresholds for each feature as most of the works in this research area do, we use Random Forest to make decision since it has been demonstrated to own better generalization ability and performance comparable to SVM or Boosting in classification problem. Another important reason we adopt Random Forest is that it has natural parallelism structure and very significant performance advantage (e. g. the overhead of training and testing the model is very low) over other popular classifiers e. g. SVM or Boosting. To the best of our knowledge, this is the first time ensemble learning strategies have been used in the area of switching median filtering. Extensive simulations are carried out on several most common standard testing images. The experimental results show that our algorithm achieves zero miss detection results while keeping the false alarm rate at a rather low level and has great superiority over other state-of-the-art methods.

关键词： Impulse noise salt-and-pepper noise noise detection switching median filter ensemble learning random forests

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The GAP Project - GPU for Realtime applications in High Energy Physics and Medical imaging

The GAP Project - GPU for Realtime Applications in High Ener...

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60th IEEE Nuclear Science Symposium (NSS) / Medical imaging conference (MIC) / 20th International Workshop on Room-Temperature Semiconductor X-ray and Gamma-ray Detectors

作者： Ammendola, R. Bauce, M. Biagioni, A. Fantechi, R. Fiorini, M. Giagu, S. Graverini, E. Lamanna, G. Lonardo, A. Messina, A. Pantaleo, F. Piandani, R. Rescigno, M. Simula, F. Sozzi, M. Vicini, P. Ist Nazl Fis Nucl Sez Roma Tor Vergata Rome Italy

ISBN: (纸本)9781479905348

We describe a pilot project for the use of GPUs (Graphics processing Units) in online triggering applications for high energy physics experiments. Two major trends can be identified in the development of trigger and DAQ systems for particle physics experiments: the massive use of general-purpose commodity systems for data acquisition, such as commercial multicore PC farms, and the reduction of trigger levels implemented in hardware, aimed at a pure software selection system (trigger-less). The very innovative approach presented here aims at exploiting the parallel computing power of commercial GPUs to perform fast software-based computations both in early trigger stages and in high level triggers. General-purpose computing on GPUs is emerging as a new paradigm in several scientific fields. So far, however, GPU applications have only been tailored in order to accelerate offline computation. With the steady reduction of GPU latencies, and the increase in link and memory throughput, such devices have become mature for use in realtime applications in high energy physics data acquisition and trigger systems. We will discuss in detail the use of online parallel computing on GPUs for synchronous low level fixed. latency triggers. We will discuss the preliminary results of a first field test within the NA62 experiment at CERN. The use of GPUs in high level triggers will be also discussed. The ATLAS experiment at CERN, and in particular its muon trigger, will be taken as a case study for possible applications.

关键词： Graphics processing unit

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