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Image compression by orthogonal decomposition and dynamic segmentation using cellular nonlinear network chips

Image compression by orthogonal decomposition and dynamic se...

引用

IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： T. Sziranyi L. Czuni I. Kopilovic T. Gyimesi Analogical and Neural Computing Laboratory Hungarian Academy of Sciences Computer and Automation Institute Budapest Hungary Department of Image Processing 8z Neurocomputing University of Veszprém Veszprem Hungary

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.

关键词： Image coding Image segmentation Discrete cosine transforms Cellular neural networks Object oriented modeling Optimization methods computer networks Distortion measurement Nonlinear distortion Very large scale integration

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Diminishment and enlargement of binary pictures using slightly space variant cellular neural network architecture

Diminishment and enlargement of binary pictures using slight...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： C. Rekeczky I. Ushida T. Roska Department of Electrical and Electronics Engineering Faculty of Engineering University of Tokushima Tokushima Japan Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Size modification of binary pictures can be mapped onto the CNN array using space variant linear templates. However, if all the parameters have to be set for each cell individually, then one of the CNN's main advantages will be lost in practice, the simple and quick parallel reprogrammability. In this paper, a general methodology is presented to derive the space variant templates of the complete weighting matrix from control pictures applying a simple nonlinear space invariant template. The straightforward design method presumes a modified CNN architecture (multiple input and specific nonlinear voltage-controlled current sources in every cell) and can be extended for a large class of sparse weighting matrices. Following this strategy the diminishment and enlargement process has been investigated using constant cell current and various bias maps in the transformations.

关键词： Cellular neural networks Optical sensors Process control Output feedback Control systems

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Image inpainting methods by using CELLULAR neural networks

Image inpainting methods by using CELLULAR neural networks

引用

9th IEEE International Workshop on Cellular neural Networks and their Applications, CNNA

作者： Gacsádi, Alexandra Szolgay, Péter Electronics Department University of Oradea Str. Armatei Române Nr.5 410087 Oradea Romania Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B.63 H-1502 Budapest Hungary Image Processing and Neurocomputing Department Veszprém University Egyetem u. 10 Veszprém Hungary

Some CNN methods are presented that can be used for the reconstruction of damaged or partially known images. The proposed methods take the possibility of direct implementation on an existing CNN chip into account, in a single step, by using 3*3 dimensional linear reaction templates. Due to complete parallel processing, computational time reduction is achieved. Efficiency of these methods can be increased by combining them with nonlinear template that ensures the growth of the local properties spreading area along with regional ones.

关键词： Cellular neural networks

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CNNUM-Based Methods Using Deformable Contours on Smooth Boundaries

CNNUM-Based Methods Using Deformable Contours on Smooth Boun...

引用

IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Tamas Szabo Peter Szolgay Department of Image Processing and Neurocomputing Faculty of Information Technology University of Pannonia Veszprem Hungary Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this paper two methods are presented. A CNNUM-based method is shown to quantify the displacement of the normal interhemisperic bilateral symmetry line. The method uses a deformable open contouring technique. Anothe... 详细信息

关键词： Active contours Computed tomography Magnetic resonance Anatomical structure Image segmentation Biomedical imaging Electronic mail computer networks Pixel Image resolution

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Image inpainting methods by using cellular neural networks

Image inpainting methods by using cellular neural networks

引用

IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： A. Gacsadi P. Szolgay Electronics Department University of Oradea Oradea Romania Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Image Processing and Neurocomputing Department Veszprem University Veszprem Hungary

关键词： Cellular neural networks Image processing Image restoration Partial differential equations Image reconstruction Parallel processing Concurrent computing Cost function Gray-scale Laboratories

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computing on silicon with trigger waves: experiments on CNN-UM chips

Computing on silicon with trigger waves: experiments on CNN-...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： C. Rekeczky I. Szatmari P. Foldesy Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Jedlik Laboratories Department of Information Technology Péter Pazmány Catholic University Budapest Hungary

ISBN: (纸本)0780366859

In this paper, experimental results on Cellular neural Network Universal Machine (CNN-UM) chips will be presented. These analogic spatio-temporal visual microprocessors make it possible that one can use nonlinear waves as the basic kernels of algorithms solving filtering-reconstruction and/or detection-classification problems. Showing output results from series of experiments it will be demonstrated how trigger waves, the simplest nonlinear waves, can constructively be used in a number of important application areas.

关键词： Silicon Cellular neural networks Shape Active contours Laboratories Microprocessors Object detection Image reconstruction Echocardiography automation

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A fast, complex and efficient test implementation of the CNN Universal Machine

A fast, complex and efficient test implementation of the CNN...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： J.M. Cruz L.O. Chua T. Roska Electronics Research Laboratory and Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Electronics Research Laboratory University of California Berkeley CA USA

In this paper we report on a fast, complex and efficient implementation of the Cellular neural Network Universal Machine as an IC chip. The chip has continuous time analog dynamics, and has been designed to process 50... 详细信息

关键词： Testing Cellular neural networks Turing machines Voltage Laboratories USA Councils Analog memory Logic circuits Programmable logic arrays Capacitors

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Multigrid MRF based picture segmentation with cellular neural networks 7th

Multigrid MRF based picture segmentation with cellular neura...

引用

7th International Conference on computer Analysis of Images and Patterns, CAIP 1997

作者： Czúni, Lázló Szirányi, Tamás Zerubia, Josiane University of Veszprém Dep. of Image Processing and Neurocomputing Egyetem u. 10 VeszprémH-8200 Hungary Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences H-11 t 1 Budapest Kende u. 13-17 Hungary NRIA Sophia-Antipolis BP 93 2004 route des Lucioles Sophia-Antipolis Cedex06902 France

ISBN: (纸本)3540634606

Due to the large computation power needed in image processing methods based on Markovian Random Field (MRF) [6], new variations of basic MRF models are implemented. The Cellular neural Network [5,14,15] (CNN) architecture, implemented in real VLSI circuits, is of superior speed in image processing. This very fast CNN can implement the ideas of existing MRF models. which would result in real-time processing of images. On the other hand this VLSI solution gives new tasks since the CNN has a special local architecture [4], but it is already shown that a type of MRF image segmentation with Modified Metropolis Dynamics (MMD [9]) can be well implemented in the CNN architecture [18]. In this paper, we address the improvement of the existing CNN method [ 17]. We have tested different multigrid models and compared segmentation results. The main reason for this research is to find proper implementation of the CNN-MRF technique on CNNs taking into consideration the abilities of today's and future's VLSI CNN systems. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Cellular neural networks

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A comparison of the different CNN implementations in solving the problem of spatiotemporal dynamics in mechanical systems

A comparison of the different CNN implementations in solving...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： P. Szolgay T. Hidvegi Z. Szolgay P. Kozma Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Mechanics Technical University of Budapest Budapest Hungary Image processing and Neurocomputing University of Veszprém Veszprem Hungary

The large computing power of cellular neural networks (CNNs) is used to compute the transient response of a mechanical vibrating system. A basic question is how an inhomogeneous mechanical system can be computed by using different CNNUM (cellular neural net Universal Machine ) implementations. How complexity to time transformations were used in different CNNUM implementations, namely in software, in emulated digital CNN chips and in analog chips is discussed.

关键词： Cellular neural networks Spatiotemporal phenomena Mechanical systems computer networks Equations Damping Boundary conditions Laboratories automation Transient response

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Non-linear scale-selection for image compression improvement obtained by perceptual distortion criteria

Non-linear scale-selection for image compression improvement...

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International Conference on Image Analysis and Processing

作者： I. Kopilovic T. Sziranyi Department of Image Processing and Neurocomputing University of Veszprém Veszprem Hungary Analogical and Neural Computing Laboratory Computer & Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Image Processing and Neurocomputing University of Veszprém Hungary

The effect of linear and nonlinear diffusions prior to the Joint Photographic Experts Group (JPEG) standard baseline compression is analysed and compared. We shall show that anisotropic diffusion acts as an adaptive filtering that extracts and preserves the important visual information, and it will be shown how it can be used as a preprocessing method for compression artefact reduction. The selection of the appropriate preprocessing parameters at a specified bit-rate greatly reduces the compression artefacts. The selection criteria were determined using a perceptual error metric based on a model of the human visual system.

关键词： Image coding Nonlinear distortion Adaptive filters Data mining Image processing Transform coding Smoothing methods Nonlinear equations Noise shaping Filtering

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