Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flatpanel detector orbiting in a circular trajectory. image reconstruction in these systems is usually performed by appr...
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Thanks to the recent technological advances, a large variety of image data is at our disposal with variable geometric, radiometric and temporal resolution. In many applications the processing of such images needs high...
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ISBN:
(纸本)9780819492791
Thanks to the recent technological advances, a large variety of image data is at our disposal with variable geometric, radiometric and temporal resolution. In many applications the processing of such images needs high performance computing techniques in order to deliver timely responses e. g. for rapid decisions or real-time actions. Thus, parallel or distributed computing methods, Digital Signal Processor (DSP) architectures, Graphical processing Unit (GPU) programming and Field-Programmable Gate Array (FPGA) devices have become essential tools for the challenging issue of processing large amount of geo-data. The article focuses on the processing and registration of large datasets of terrestrial and aerial images for 3D reconstruction, diagnostic purposes and monitoring of the environment. For the image alignment procedure, sets of corresponding feature points need to be automatically extracted in order to successively compute the geometric transformation that aligns the data. The feature extraction and matching are ones of the most computationally demanding operations in the processing chain thus, a great degree of automation and speed is mandatory. The details of the implemented operations (named LARES) exploiting parallel architectures and GPU are thus presented. The innovative aspects of the implementation are (i) the effectiveness on a large variety of unorganized and complex datasets, (ii) capability to work with high-resolution images and (iii) the speed of the computations. Examples and comparisons with standard CPU processing are also reported and commented.
Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. image reconstruction in these systems is usually performed by app...
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Software pipelining is an instruction-level loop scheduling method for achieving high performance fine-grain parallelism on VLIW (very long instruction word) processors. This paper presents a novel software pipelining...
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ISBN:
(纸本)9539676940
Software pipelining is an instruction-level loop scheduling method for achieving high performance fine-grain parallelism on VLIW (very long instruction word) processors. This paper presents a novel software pipelining method for non-pipelining parallel processors based on integer scaling and retiming transformations. This approach generalises and simplifies the analogous extended retiming model of T.W. O'Neil et al. (see Proc. ISCA 12th Int. Conf. parallel & distributed Computing Syst., p.292-7, 1999; Proc. of ICASSP'99 Conf., vol.4 p.2001-4, 1999). Matrix techniques are used in order to simplify the corresponding graph transformations. Some general properties taken from algebraic graph theory are applied in order to obtain general scheduling techniques: node and cycle methods. The two-phase scheduling method considered is first defined by means of two standard linear programming problems. We transform the corresponding problems into some variants of the maximum cost-to-time ratio problem and shortest path problem, in order to obtain efficient polynomial time algorithms. An example of software pipelining optimization of a digital correlator is also given.
Projection is a frequently used process in imageprocessing and visualization. In volume graphics, projection is used to render the essential content of a 3D volume onto a 2D image plane. For Radon transform, projecti...
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ISBN:
(纸本)0819433039
Projection is a frequently used process in imageprocessing and visualization. In volume graphics, projection is used to render the essential content of a 3D volume onto a 2D image plane. For Radon transform, projection is used to transform the image space into a parameter space. In this paper, we propose a matrix decomposition method called identity-plus-row decomposition for designing fast algorithms for projections. By applying this method, we solve the data redistributed problem due to the irregular data access patterns present in those applications on SIMD mesh-connected computers, developing fast algorithms for volume rendering and Radon transform an SIMD mesh-connected computers.
A real-time distributedimageprocessing system requires data transfer, synchronization and error recovery. However, it is difficult for a programmer to describe these mechanisms. To solve this problem, we are develop...
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A real-time distributedimageprocessing system requires data transfer, synchronization and error recovery. However, it is difficult for a programmer to describe these mechanisms. To solve this problem, we are developing a programming tool for real-time imageprocessing on a distributed system. Using the programming tool, a programmer indicates only data flow between computers and imageprocessing algorithms on each computer. In this paper, we outline specifications of the programming tool and show sample programs on the programming tool.
In this paper we describe AIDPG, an interactive prototype system, which derives computer programs from their natural language descriptions. AIDPG shows how to analyze natural language, resolve ambiguities using knowle...
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ISBN:
(纸本)0819433039
In this paper we describe AIDPG, an interactive prototype system, which derives computer programs from their natural language descriptions. AIDPG shows how to analyze natural language, resolve ambiguities using knowledge, and generates programs. AIDPG consists of a natural language input model (NLI-Model), a natural language analysis model (NLA-Model), a program generation model (PGG-Model) and a human machine interface control model (HMC-Model). The PGG model has three sub-models, program structure manage sub-model, a data structure and type manage sub-model, and program base manage sub-model. We used an arithmetic problem, which, described in Japanese, was passed to AIDPG and got run-possible C programs. Although AIDPG is basic currently we got a significant result.
The Karhunen-Loeve(K-L) transform is very useful in image representation and classification. However, the parallel implementation of it through some optical methods have rarely been investigated. In this paper, we con...
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The Karhunen-Loeve(K-L) transform is very useful in image representation and classification. However, the parallel implementation of it through some optical methods have rarely been investigated. In this paper, we constructed a photorefractive crystal based optical processor and implemented the time-consuming projection and operations of the K-L transform in parallel so that the speed of the imageprocessing can be greatly improved. In our approach, a set of eigenimages extracted from a large number of training images by K-L transform are stored in the crystal by using the two-wave mixing technique. When any view image inputs the processor, spatially separated beams with different light intensities are obtained in parallel. The intensity of each beam just represents the projection result between the input image and each eigenimage. The high speed can sufficiently demonstrate the advantage of the optical computing based parallel architecture for imageprocessing.
One major difficulty in designing an architecture for the parallel implementation of Discrete Wavelet Transform (DWT) is that the DWT is not a block transform. As a result, frequent communication has to be set up betw...
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ISBN:
(纸本)0819433039
One major difficulty in designing an architecture for the parallel implementation of Discrete Wavelet Transform (DWT) is that the DWT is not a block transform. As a result, frequent communication has to be set up between processors to exchange data so that correct boundary wavelet coefficients can be computed. The significant communication overhead thus hampers the improvement of the efficiency of parallel systems, specially for processor networks with large communication latencies. In this paper we propose a new technique, called Boundary Postprocessing, that allows the correct transform of boundary samples. The basic idea is to model the DWT as a Finite State Machine (FSM) based on the lifting factorization of the wavelet filterbanks. Application of this technique leads to a new parallel DWT architecture, Sg,lit-and-Merge, which requires data to be communicated only once between neighboring processors for any arbitrary level of wavelet decompositions. Example designs and performance analysis for 1D and 2D DWT show that the proposed technique can greatly reduce the interprocessor communication overhead. As an example, in a two-processor case our proposed approach shows an average speedup of about 30% as compared to best currently available parallel computation.
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