随着卫星遥感获取技术的发展,影像数据量呈几何式增长,传统数据存储技术已经无法适应海量影像数据的处理要求。结合金字塔模型和MapReduce架构提出了一种适用于云计算环境的分布式并行存储方法—BMLStorage(storage based on MapReduce ...
详细信息
随着卫星遥感获取技术的发展,影像数据量呈几何式增长,传统数据存储技术已经无法适应海量影像数据的处理要求。结合金字塔模型和MapReduce架构提出了一种适用于云计算环境的分布式并行存储方法—BMLStorage(storage based on MapReduce and local file system),该方法基于金字塔模型对影像数据进行分层分块处理,并对所得瓦片重新编码。定义了一种新的存储规则,使得所有瓦片可以按照此规则利用Hadoop中的MapReduce框架实现并行存储。实验表明,该方法与现有方法相比,在海量影像数据存储性能方面有一定的提高。
Background: Automated image analysis on virtual slides is evolving rapidly and will play an important role in the future of digital pathology. Due to the image size, the computational cost of processing whole slide im...
详细信息
Background: Automated image analysis on virtual slides is evolving rapidly and will play an important role in the future of digital pathology. Due to the image size, the computational cost of processing whole slide images (WSIs) in full resolution is immense. Moreover, image analysis requires well focused images in high magnification. methods: We present a system that merges virtual microscopy techniques, open source image analysis software, and distributedparallelprocessing. We have integrated the parallelprocessing framework JPPF, so batch processing can be performed distributed and in parallel. All resulting meta data and image data are collected and merged. As an example the system is applied to the specific task of image sharpness assessment. imageJ is an open source image editing and processing framework developed at the NIH having a large user community that contributes imageprocessing algorithms wrapped as plug-ins in a wide field of life science applications. We developed an imageJ plug-in that supports both basic interactive virtual microscope and batch processing functionality. For the application of sharpness inspection we employ an approach with non-overlapping tiles. Compute nodes retrieve image tiles of moderate size from the streaming server and compute the focus measure. Each tile is divided into small sub images to calculate an edge based sharpness criterion which is used for classification. The results are aggregated in a sharpness map. Results: Based on the system we calculate a sharpness measure and classify virtual slides into one of the following categories - excellent, okay, review and defective. Generating a scaled sharpness map enables the user to evaluate sharpness of WSIs and shows overall quality at a glance thus reducing tedious assessment work. Conclusions: Using sharpness assessment as an example, the introduced system can be used to process, analyze and parallelize analysis of whole slide images based on open source software.
The edge-directed interpolation scheme is a noniterative, orientation-adaptive method to enhance image resolution with better visual effect than conventional interpolation methods. It interpolates the missing pixels b...
详细信息
ISBN:
(纸本)9780769545769
The edge-directed interpolation scheme is a noniterative, orientation-adaptive method to enhance image resolution with better visual effect than conventional interpolation methods. It interpolates the missing pixels based on the covariance of a high-resolution image estimated from the covariance of the low-resolution image. In spite of the impressive performance, the computational complexity of covariance-based adaptation is significantly higher than that of the conventional linear interpolation algorithms. In this paper, we propose a GPU-based massively parallel version of the edge-directed interpolation scheme. A speedup of 61.7x can be achieved with respect to its single-threaded CPU counterpart in the host computer.
The aim of this work is to solve the image retrieval problems with modern methods of numerical linear algebra, which can be easily parallelized for distributed memory architectures like a cluster platform. Algorithm p...
详细信息
ISBN:
(纸本)9781905088423
The aim of this work is to solve the image retrieval problems with modern methods of numerical linear algebra, which can be easily parallelized for distributed memory architectures like a cluster platform. Algorithm presented in this paper is singular value decomposition (SVD). We show that SVD is directly linked with information retrieval through latent semantic indexing. However, our main concern is efficiency of computations of SVD. We present our parallel implementation of Householder bidiagonalization, which we consider the most computationally demanding step of singular value decomposition. We shall also compare our proposed algorithms with commonly used approaches on the experiments, and we shall emphasize their advatages in sence of usage of standard optimized linear algebra packages.
We investigate dual decomposition approaches for optimization problems arising in low-level vision. Dual decomposition can be used to parallelize existing algorithms, reduce memory requirements and to obtain approxima...
详细信息
We investigate dual decomposition approaches for optimization problems arising in low-level vision. Dual decomposition can be used to parallelize existing algorithms, reduce memory requirements and to obtain approximate solutions of hard problems. An extensive set of experiments are performed for a variety of application problems including graph cut segmentation, curvature regularization and more generally the optimization of MRFs. We demonstrate that the technique can be useful for desktop computers, graphical processing units and supercomputer clusters. To facilitate further research, an implementation of the decomposition methods is made publicly available. (C) 2011 Elsevier Inc. All rights reserved.
The proceedings contain 28 papers. The topics discussed include: using a commercial graphical processing unit and the CUDA programming language to accelerate scientific imageprocessing applications;automatic distribu...
ISBN:
(纸本)9780819484093
The proceedings contain 28 papers. The topics discussed include: using a commercial graphical processing unit and the CUDA programming language to accelerate scientific imageprocessing applications;automatic distribution of vision-tasks on computing clusters;highly scalable digital front end architectures for digital printing;parallel training and testing methods for complex imageprocessing algorithms on distributed, heterogeneous, unreliable, and non-dedicated resources;integrated parallel printing systems with hypermodular architecture;parallelprocessing considerations for image recognition tasks;GPGPU real-time texture analysis framework;a novel parallel algorithm for airport runway segmentation in satellite images using priority directional region growing strategy based on ensemble learning;visualization assisted by parallelprocessing;and a parallel impulse-noise detection algorithm based on ensemble learning for switching median filters.
Stencil calculations comprise an important class of kernels in many scientific computing applications ranging from simple PDE solvers to constituent kernels in multigrid methods as well as imageprocessing application...
详细信息
During the present decade, emerging architectures like multicore CPUs and graphics processing units (GPUs) have steadily gained popularity for their ability to deploy high computational power at a low cost. In this pa...
详细信息
Retinex is one of the well-known schemes for adaptive image enhancement under poor weather conditions. Improving the visibility of input images on a target detection system is necessary to insure detection work proper...
详细信息
暂无评论