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Titlebook: Signal Processing for Computer Vision; Gösta H. Granlund,Hans Knutsson Book 1995 Springer Science+Business Media Dordrecht 1995 Adaptive F

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书目名称Signal Processing for Computer Vision
编辑Gösta H. Granlund,Hans Knutsson
视频videohttp://file.papertrans.cn/868/867077/867077.mp4
图书封面Titlebook: Signal Processing for Computer Vision; Gösta H. Granlund,Hans Knutsson Book 1995 Springer Science+Business Media Dordrecht 1995 Adaptive F
描述.Signal Processing for Computer Vision. is a unique andthorough treatment of the signal processing aspects of filters andoperators for low-level computer vision. .Computer vision has progressed considerably over recent years. Frommethods only applicable to simple images, it has developed to dealwith increasingly complex scenes, volumes and time sequences. Asubstantial part of this book deals with the problem of designingmodels that can be used for several purposes within computer vision.These partial models have some general properties of invariancegeneration and generality in model generation. ..Signal Processing for Computer Vision. is the first book to givea unified treatment of representation and filtering of higher orderdata, such as vectors and tensors in multidimensional space. Includedis a systematic organisation for the implementation of complex modelsin a hierarchical modular structure and novel material on adaptivefiltering using tensor data representation. ..Signal Processing for Computer Vision. is intended for final yearundergraduate and graduate students as well as engineers andresearchers in the field of computer vision and image processing..
出版日期Book 1995
关键词Adaptive Filter; Adaptive filtering; Phase; Signal; computer; computer vision; filtering; image processing;
版次1
doihttps://doi.org/10.1007/978-1-4757-2377-9
isbn_softcover978-1-4419-5151-9
isbn_ebook978-1-4757-2377-9
copyrightSpringer Science+Business Media Dordrecht 1995
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Biological Vision,ery flexible and highly integrated system for human vision. Although it has not, in general, proved feasible to employ biological functions for technical systems, the situation may be quite different in the field of information processing. The computational structures which have been developed in ou
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Low Level Operations,ich are contiguous areas of memory with data elements laid out one after the other. The storage layout of arrays simplifies data access when all items are elements in regular arrays. Then the program merely needs to take the position of the element and multiply the .-coordinate by the row length, an
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Kernel Optimization,tricted to the case where the desired ideal filter is given in the Fourier domain. An optimal kernel is the set of coefficients that minimizes some distance measure with respect to the ideal filter. A family of distance measures suitable for multidimensional image signals is given. The dependence of
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Local Frequency,ructure analysis as well as for determining the appropriate range of scales for subsequent processing. The method is based on combining local estimates of instantaneous frequency over a large number of scales. The filters used are a set of lognormal quadrature filters. The bandwidth is used to produ
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Texture Analysis, recognition. Computer vision researchers have used measures of texture to segment scenes and discriminate between different objects. Psychophysicists have studied texture for knowledge about human low-level visual information processing. It has been assumed that a solution to the texture analysis p
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