Xem 1-13 trên 13 kết quả Spatial filtering
  • Digital Image Processing: Image Enhancement Spatial Filtering - Duong Anh Duc includes Image Enhancement - Spatial Filtering; How to specify T; Smoothing Filters; Image smoothing by averaging (lowpass spatial filtering); Image Sharpening; High-boost filtering; Prewitt operators.

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: From Matched Spatial Filtering towards the Fused Statistical Descriptive Regularization Method for Enhanced Radar Imaging

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  • Systems designed to receive spatially propagating signals often encounter the presence of interference signals. If the desiredsignal andinterferers occupy the same temporal frequency band, thentemporal filtering cannot be usedto separate signal frominterference.

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  • Lecture Digital image processing - Spatial and frequency domain filter design include all of the following content: Spatial domain filter design (average/mean filter, median filter, gaussian smoothing, conservative smoothing), frequency – based filter design.

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  • PROPAGATION OF LIGHT IN FREE SPACE A. Correspondence Between the Spatial Harmonic and the Plane Wave B. Transfer Function of Free Space C. Impulse-Response Function of Free Space OPTICAL FOURIER TRANSFORM A. Fourier Transform in the Far Field B. Fourier Transform Using a Lens DIFFRACTION OF LIGHT A. Fraunhofer Diffraction *B. Fresnel Diffraction IMAGE FORMATION A. Ray-Optics Description of Image Formation B. Spatial Filtering C. Single-Lens Imaging System HOLOGRAPHY

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  • Systems designed to receive spatially propagating signals often encounter the presence of interference signals. If the desiredsignal andinterferers occupy the same temporal frequency band, thentemporal filtering cannot be usedto separate signal frominterference. However, desiredandinterfering signals often originate fromdifferent spatial locations. This spatial separation can be exploited to separate signal frominterference using a spatial filter at the receiver.

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  • CO measurement options include bag collection and lab analysis, colour-change diffusion tubes and electro-chemical monitors. PM measurement options include gravimetric monitors (pump and filter method) and light-scattering devices. The advantages and disadvantages of each of these methods are discussed, including cost, ease-of-use, accuracy, size detection and time-keeping. The choice of method depends on the context, i.e. the purpose of the project or programme, the capacity of staff and available financial and human resources.

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  • The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octavescale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The DWT algorithms were initially based on the compactly supported conjugate quadrature filters (CQFs). However, a drawback in CQFs is due to the nonlinear phase effects such as spatial dislocations in multi-scale analysis.

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  • DWTs are constantly used to solve and treat more and more advanced problems. The DWT algorithms were initially based on the compactly supported conjugate quadrature filters (CQFs). However, a drawback in CQFs is due to the nonlinear phase effects such as spatial dislocations in multi-scale analysis. This is avoided in biorthogonal discrete wavelet transform (BDWT) algorithms, where the scaling and wavelet filters are symmetric and linear phase. The biorthogonal filters are usually constructed by a ladder-type network called lifting scheme.

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  • Digital signal processing is currently in a period of rapid growth caused by recent advances inVLSI technology. This is especially true of three areas of optimum signal pro- cessing; namely, real-time adaptive signal processing, eigenvector methods of spectrum estimation, and parallel processor implementations of optimum filtering and prediction algorithms. In this edition the book has been brought up to date by increasing the emphasis on the above areas and including several new developments.

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  • Two-Dimensional Filters What is this chapter about? Manipulation of images often entails omitting or enhancing details of certain spatial frequencies. This is equivalent to multiplying the Fourier transform of the image with a certain function that “kills” or modifies certain frequency components. When we do that, we say that wefilter the image, and the function we use is called a filter.

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  • Event recognition methods can be roughly categorized into model-based methods and appearance-based techniques. Model-based approaches relied on various models, includ- ing HMM [35], coupled HMM [3], and Dynamic Bayesian Network [33], to model the temporal evolution. The relationships among different body parts and regions are also modeled in [3], [35], in which object tracking needs to be conducted at first before model learning.

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  • Lecture Digital image processing include the content: Introduction to Image processing and matlab; image acquisition, types, and file I/O; image arithmetic; spatial and frequency domain filter design; mage restoration and blind deconvolution;...

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