Parallel Architectures for Image Processing.
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- Published Date: 01 Jul 1990
- Publisher: Society of Photo Optical
- Language: English
- Format: Paperback
- ISBN10: 0819402931
- File Name: Parallel Architectures for Image Processing.pdf
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Parallel Architectures for Image Processing download ebook. IEEE Trans Image Process. 1996;5(7):1204-8. Cache write generate for parallel image processing on shared memory architectures. Wittenbrink CM(1), Somani B. Parallel Programming Architectures. HMPP (Hybrid Multicore Parallel Programming. Environment) based on GPUs (Graphics Processing Units) can. Design of parallel algorithms and special purpose architectures for digital signal and image processing applications with emphasis on high-speed communications and computational engineering. Mapping digital signal and image processing algorithms to pipeline arrays, systolic arrays, wave-front arrays and other parallel architectures. HPC: Parallel Architecture and processing elements to be searched in parallel or to be split for the processing (image processing, map/reduce approaches) In this article, we present a new reconfigurable parallel architecture oriented to video-rate computer vision applications. This architecture is structured with a processing research. The state of the art in image recognition uses variants of the inception architecture, residual networks, and other architectures that enable many combinations of convolutional layers, while managing the combinatorial com-plexity of weights and activations. We discuss these methods in greater detail in the next section. Parallel In-Memory Processing and Data Virtualization Redefine Analytics Architectures. The tide is changing for analytics architectures. Traditional approaches The inherent parallelism in image processing and computer vision suggests that high There are significant architectural implications of this fact, primarily for extraction. An analog CCD parallel processing architecture developed An image feature extractor (IFE) device suitable for performing the inner products. Optimization of a Hyperspectral Image Processing Chain Using Heterogeneous and GPU-Based Parallel Computing Architectures Antonio J. Plaza1, Javier Plaza1, Sergio S anchez1 and Abel Paz1 1 Department of Technology of Computers and Communications, University of Extremadura, Avda. de la Universidad s/n, E-10071 Ca ceres, Spain Image processing by nature has SIMD parallelism (Single Instruction, Multiple Data). That is, the data made of millions of pixels requires a In a parallel processing topology, the workload for each job is distributed This image shows four processors that share common disk and memory resources. JPEG2000 is a relatively new image compression standard which builds and This paper proposes a Parallel Bit Plane Coding (BPC) architecture in which framework for massive hyperspectral image processing based on cloud algorithm and its distributed parallel implementation for cloud computing architectures. PARALLEL ARCHITECTURES FOR INAGE PROCESSING S t a n l e y R. S t e r n b e r g zyxwvutsrqpo Environmental Research I n s t i t u t e of Michigan Ann Arbor, Michigan A b s t r a c t - Image p r o c e s s i n g o p e r a t i o n s a r e d e f i n e d which permit image p r o c e s s i n g a l g o r i t h m s t o b e w r i t t e n as a l g e b r a A new FPGA/DSP-based parallel architecture for real-time image processing Article in Real-Time Imaging 8(5):345-356 October 2002 with 1,086 Reads How we measure 'reads' image processing to take place on the FPGA device, then for A suitable architecture for extremely parallel image processing will be recognis-. Browne [Browne, 89] discussed the various options of image processing mapping methods of this standard, and its implementation on parallel architectures. The home page for the Architecture & Language Implementation Group. Architecture & Language Implementation application-specific parallel architectures and software for heterogeneous systems. This benchmark is intended to measure the appropriateness of parallel machines for image processing. ParaScope: A Parallel Programming Environment. global masking as well as local masking for SIMD architectures constructed from standard masking efficiently in large-scale SIMD parallel processing sys- tems based on operate on an image, a PE-address mask can be used to efficiently medium level image processing on general purpose (parallel) architectures. The organization of this paper is as follows. In Section 2 some preliminaries are given. Section 3 presents de nitions of the watershed transform, both for the continuous and the discrete case. Sequential watershed algorithms are reviewed in Section 4. Section 5 contains Real-time processing of multidimensional image and video signal in- volves operating parallel and parallel-parallel architectures [74] belong to this category. processing elements (perhaps very simple ones) working on a single task. One usehl way of classifying these massively parallel architectures is by the type of we-must match the image against a set of stored. viewpoint-invariant shape. (I. In this paper, a parallel architecture for fast image processing has been used to speed up median filter and edge detection process, which are
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