Anisotropic diffusion is an image enhancement method. It is a nonlinear process which removes noise and irrelevant details while preserving the edges, i.e. it "extracts" the essential visual information. The...
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Anisotropic diffusion is an image enhancement method. It is a nonlinear process which removes noise and irrelevant details while preserving the edges, i.e. it "extracts" the essential visual information. The paper proposes a useful application of anisotropic diffusion in image data compression. We argue that for high compression an anisotropic diffusion preprocessing results in better quality of the decoded image.
Anisotropic diffusion is an image enhancement method. It is a nonlinear process which removes noise and irrelevant details while preserving the edges, i.e. it "extracts" the essential visual information. The...
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A method is shown using the CNN chip-set hardware architecture for the implementation of a high-speed, low bit-rate image coding system. A simple and fast algorithm is introduced to generate basis functions of 2 dimen...
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A method is shown using the CNN chip-set hardware architecture for the implementation of a high-speed, low bit-rate image coding system. A simple and fast algorithm is introduced to generate basis functions of 2 dimensional (2D) orthogonal transformations. Using the 2D basis functions of the Hadamard or Cosine functions, the transformation coefficients of the basic block of the image are measured by the CNN. Meanwhile, the CNN can produce the inverse transformation of the measured coefficients and the actual distortion-rate can be computed. If a required distortion-rate is reached, the coding process could be stopped (the use of even more coefficients would increase bit-rate needlessly). Effects of noise and VLSI computing accuracy are also considered to optimise the architecture. We also give a short description of how to join the transform coding method and the object-oriented image model.
Printed circuit board layout inspection methods are mostly based on local geometric information, therefore they are well suited to the cellular neural networks (CNN) paradigm. The wire break, the wire and isolation wi...
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Printed circuit board layout inspection methods are mostly based on local geometric information, therefore they are well suited to the cellular neural networks (CNN) paradigm. The wire break, the wire and isolation width violation and an "H" type short circuits detector analogic algorithms were tested on a 20*22 CNN Universal Machine (CNNUM) chip working in the CNN Chip Prototyping System (CCPS) and on the CNN Engine Board (CNNEB), and the results were compared to the commercially available inspection systems.
Due to the large computation power needed for Markovian random field (MRF) based imageprocessing, new variations of the basic MRF model are implemented. The transportation of the model to the very fast cellular neura...
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Due to the large computation power needed for Markovian random field (MRF) based imageprocessing, new variations of the basic MRF model are implemented. The transportation of the model to the very fast cellular neura...
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Due to the large computation power needed for Markovian random field (MRF) based imageprocessing, new variations of the basic MRF model are implemented. The transportation of the model to the very fast cellular neural networks (CNN) gave new tasks and opportunities to improve the technique, since the CNN has a special local architecture. This CNN architecture can be implemented in real VLSI circuits of superior speed in imageprocessing. A type of MRF image segmentation with modified metropolis dynamics (MMD) can be well implemented in the CNN architecture. In this paper we address the improvement of this existing CNN method by introducing anisotropic diffusion as the smoothing process in the model. We suggest that this new feature with the MRF representation will give a new approach to solving early vision problems in the future.
The printed circuit board layout inspection methods are mostly based on local geometric information, therefore it is well suited to the cellular neural network (CNN) paradigm. Two layout errors are detected here namel...
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The printed circuit board layout inspection methods are mostly based on local geometric information, therefore it is well suited to the cellular neural network (CNN) paradigm. Two layout errors are detected here namely, the breaks in the wires and some kind of short circuits. The designed analogic algorithms to solve the problems above were tested on real life examples using an experimental system based on our CNN-HAC1M digital multiprocessor add-on-board, with 1 million cell space and 2.0 /spl mu/s/cell/iteration speed.
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