A class of Finite Impulse Response (FIR) filtering algorithms based either on short Fast Fourier Transforms (FFT) or on short length FIR filtering algorithms was recently proposed. Besides the significant reduction of...
A class of Finite Impulse Response (FIR) filtering algorithms based either on short Fast Fourier Transforms (FFT) or on short length FIR filtering algorithms was recently proposed. Besides the significant reduction of the arithmetic complexity, these algorithms present some characteristics which make them useful in many applications, namely a small delay processing (independent on the FIR filter length) as well as a multiply-add based computational structure. These algorithms are presented in a unified framework, thus allowing an easy combination of any of them. However, a remaining difficulty concerns the implementation of the fast algorithms on Digital Signal Processors (DSP), given the DSP finite resources (number of pointers, registers and memory), while keeping as much as possible the improvement brought by the reduction of the arithmetic complexity. This paper provides an efficient implementation methodology, by organizing the algorithm in such a way that the memory data access is optimized on a DSP. As a result, our implementation requires a constant number of pointers whatever the algorithm combination. This knowledge is used in a DSP code generator which is able to select the appropriate algorithm meeting the application constraints, as well as to generate automatically an optimized assembly code, using macro-instructions available in a DSP-dependent library. An improvement of more than 50% in terms of throughput (number of machine cycles per point) compared to the implementation of the direct convolution is generally achieved.
Motion-compensated estimation is an effective means in reducing the interframe correlation for image sequence coding. Therefore, it is adopted by the international video coding standards, ITU H.261, H.263, ISO MPEG-1 ...
Motion-compensated estimation is an effective means in reducing the interframe correlation for image sequence coding. Therefore, it is adopted by the international video coding standards, ITU H.261, H.263, ISO MPEG-1 and MPEG-2. This paper provides a comprehensive survey of the motion estimation techniques that are pertinent to video coding standards. There are three popular groups of motion estimation methods: i) block matching methods, ii) differential (gradient) methods, and iii) Fourier methods. However, not all of them are suitable for the block-based motion compensation structure specified by the aforementioned standards. Our focus in this paper is to review those techniques that would fit into the standards. In addition to the basic operations of these techniques, issues discussed are their extensions, their performance limit, their relationships with each other, and the other advantages or disadvantages of these methods. At the end, an example of evaluating block matching algorithms from a system-level VLSI design viewpoint is provided.
This paper presents a unified algorithm of blind source separation based on the "Independent Component Analysis"(ICA) principle. The algorithm can separate all sources provided there is at most one Gaussian ...
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This paper presents a unified algorithm of blind source separation based on the "Independent Component Analysis"(ICA) principle. The algorithm can separate all sources provided there is at most one Gaussian distributed source. The key point is to find a matrix by which the estimates of the original signals are pairwise independent in the absence of noises. If the observed signals are corrupted by noises, minimum-variance unbiased estimates are obtained. In comparison with the algorithm proposed previously by the authors, this algorithm has a parallel pipeline structure, and will not need a preset threshold if both of the 3rd- and 4th-order cumulants of any non-Gaussian distributed source are not zero. This algorithm has significant advantages over existing algorithms.
The traditional fuzzy objective-function-based clustering algorithms, the fuzzy c-means (FCM) algorithm and the FCM-type algorithms, are in essence local search techniques that search for the optimum by using a hill-c...
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ISBN:
(纸本)0780324617
The traditional fuzzy objective-function-based clustering algorithms, the fuzzy c-means (FCM) algorithm and the FCM-type algorithms, are in essence local search techniques that search for the optimum by using a hill-climbing technique. Thus, they often fail in the search for global optimum. In this paper, we combine the genetic algorithms with traditional clustering algorithms to obtain a better clustering performance. Our experimental results show that the proposed genetic-based clustering algorithms have much higher probabilities of finding the global or near-global optimal solutions than the traditional algorithms.< >
Discusses the problem of using visual and other sensors in the manipulation of a part by a robotic manipulator in a manufacturing workcell. The authors' emphasis is on the part localization problem involved. The a...
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Discusses the problem of using visual and other sensors in the manipulation of a part by a robotic manipulator in a manufacturing workcell. The authors' emphasis is on the part localization problem involved. The authors introduce a new sensor-fusion approach which fuses sensory information from different sensors at various spatial and temporal scales. Relative spatial information obtained from processing of visual information is mapped to absolute taskspace of the robot through fusing of information from an encoder. Data obtained this way can be superimposed upon data obtained from displacement based vision algorithms at coarser time scales to improve overall reliability. Tracking plans reflecting sensor fusion are proposed. The localization of a part by spatial sensor fusion is experimentally demonstrated to be able to give required fast and accurate part localization.
Finding the best adequacy of architectures and algorithms for low and intermediate imageprocessing is the central problem of design of any system dedicated to imageprocessing. This paper analyses some image processi...
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Finding the best adequacy of architectures and algorithms for low and intermediate imageprocessing is the central problem of design of any system dedicated to imageprocessing. This paper analyses some image processi...
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Finding the best adequacy of architectures and algorithms for low and intermediate imageprocessing is the central problem of design of any system dedicated to imageprocessing. This paper analyses some imageprocessingalgorithms in order to define pertinent invariants in imageprocessing. It includes the data types used, and the evolution of their representation during the processing and data movements. The common, but essential, characteristics are used for the definition of the most suitable architectural invariants-basic elements for any machine dedicated to imageprocessing. Some implementations of several invariants on some existing massively parallel architectures are also discussed.< >
A great number of parallel computer architectures have been proposed, whether they are SIMD machines (Single Instruction Multiple Data) with lots of quite simple processors, or MIMD machines (Multiple Instruction Mult...
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ISBN:
(纸本)0819412775
A great number of parallel computer architectures have been proposed, whether they are SIMD machines (Single Instruction Multiple Data) with lots of quite simple processors, or MIMD machines (Multiple Instruction Multiple Data) containing few, but powerful processors. Each one claims to offer some kind of an optimality at the hardware level. But implementing parallel imageprocessingalgorithms to make them run in real time will remain a real challenge; it addresses rather the control of communication networks between processors (message passing, circuit switching..) or the computing model (e.g. data parallel model). In that respect, our goal here is to point out some algorithmic needs to distribute imageprocessing operators. They will be translated first in terms of programming models, more general then imageprocessing applications, and then as hardware properties of the processor network. In that way, we do not design yet another parallel machine dedicated to imageprocessing, but a more general parallel architecture which one will be able to efficiently implement different kinds of programming models.
This paper describes a method for multiresolutional representation of gray-level images as hierarchial sets of strokes characterizing forms of objects with different degrees of generalization depending on the context ...
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ISBN:
(纸本)0819410276
This paper describes a method for multiresolutional representation of gray-level images as hierarchial sets of strokes characterizing forms of objects with different degrees of generalization depending on the context of the image. This method transforms the original image into a hierarchical graph which allows for efficient coding in order to store, retrieve, and recognize the image. The method which is described is based upon finding the resolution levels for each image which minimizes the computations required. This becomes possible because of the use of a special image representation technique called Multiresolutional Attentional Representation for Recognition, based upon a feature which the authors call a stroke. This feature turns out to be efficient in the process of finding the appropriate system of resolutions and construction of the relational graph. Multiresolutional Attentional Representation for Recognition (MARR) is formed by a multi-layer neural network with recurrent inhibitory connections between neurons, the receptive fields of which are selectively tuned to detect the orientation of local contrasts in parts of the image with appropriate degree of generalization. This method simulates the 'coarse-to-fine' algorithm which an artist usually uses, making at attentional sketch of real images. The method, algorithms, and neural network architecture in this system can be used in many machine-vision systems with AI properties;in particular, robotic vision. We expect that systems with MARR can become a component of intelligent control systems for autonomous robots. Their architectures are mostly multiresolutional and match well with the multiple resolutions of the MARR structure.
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