noise reduction in ct images

Ngày tải lên: 20/06/2014, 21:20

Ngày tải lên: 20/06/2014, 23:20

Ngày tải lên: 21/06/2014, 20:20

Ngày tải lên: 20/06/2014, 22:20

Ngày tải lên: 09/08/2014, 09:21

Ngày tải lên: 13/08/2014, 11:23

... The role of language in adult education and poverty reduction in Botswana Mompoloki Bagwasi, University of Botswana Introduction Raditloaneng (2002) makes a distinction between economic ... self- esteem and minimal participation in education and little access to information or vice-versa. This paper examines the role of language in reducing poverty in a community by enhancing its self ... because it is involved in the education of the most productive, experienced and influential sector of a population. Adults are responsible for generating a community’s income, for preserving its resources...

Ngày tải lên: 05/11/2012, 16:27

... parallel processing elements are interconnected with a hierarchically structured connection network. The connection weights are trained to perform a signal processing function such as prediction or ... tract. The main source of correlation in speech is the vocal tract modelled by a linear predictor. A linear predictor forecasts the amplitude of the signal at time m, x ( m ) , using a linear ... remove the out–of–band noise. 1.3.8 Dolby Noise Reduction Dolby noise reduction systems work by boosting the energy and the signal to noise ratio of the high–frequency spectrum of audio signals....

Ngày tải lên: 21/01/2014, 07:20

... Modelling Noise The objective of modelling is to characterise the structures and the patterns in a signal or a noise process. To model a noise accurately, we need a structure for modelling ... audio- frequency noise, such as the noise from moving cars, noise from computer fans, electric drill noise and people talking in the background, has a non- white predominantly low-frequency spectrum. ... an instance of the latter. In order for noise voltage to be developed in a conductor, magnetic lines of flux must be cut by the conductor. Electric generators function on this basic principle....

Ngày tải lên: 21/01/2014, 07:20

... parameters. Furthermore in many signal processing algorithms, such as spectral subtraction for noise reduction described in Chapter 11, or linear prediction described in Chapter 8, what we ... localised structure either in the time domain or in the frequency domain. Example 3.7 Autocorrelation and power spectrum of impulsive noise. Impulsive noise is a random, binary-state (“on/off”) ... shown in Figure 3.2. The noise on each telephone line fluctuates randomly with time, and may be denoted as n(m,s), where m is the discrete time index and s denotes the line index. The collection...

Ngày tải lên: 21/01/2014, 07:20

... reducing the variance of each class. In telecommunication systems the overlap between the signal classes is reduced using a combination of several methods including increasing the signal-to -noise ... observation vector y . Note that the centre of the posterior space is obtained by subtracting the noise mean vector from the noisy signal vector. The clean signal is then somewhere within a subspace ... convenient to obtain the likelihood function f Y | Θ ( y | θ ). The prior pdf influences the inference drawn from the likelihood function by weighting it with f Θ ( θ ) . The influence of the...

Ngày tải lên: 21/01/2014, 07:20

... either by filtering the noise from the signal (for example using the Wiener filtering and the spectral subtraction methods described in Chapters 6 and 11) or by combining the noise and the signal ... distinct, or elementary, stochastic events in a signal process. For example, in modelling a binary-state process such as impulsive noise, N is set to 2, and in isolated-word speech modelling ... training examples { X =[ x (0) , , x ( T –1)]}, with the objective of maximising f X | M ( X | M ), the likelihood of the model and the training data. The Baum–Welch method of training...

Ngày tải lên: 21/01/2014, 07:20

... perpendicular minimum distance projection of the desired signal vector onto the vector space of the input signal. A vector space is the collection of an infinite number of vectors that can be obtained ... noisy environments such as the noise inside a car emanating from the engine, aircraft noise, office noise from computer machines, etc. The main practical problem in the implementation of a Wiener ... Wiener filter. Interpretation of Wiener Filters as Projection in Vector Space 187 6.3 Interpretation of Wiener Filters as Projection in Vector Space In this section, we consider...

Ngày tải lên: 21/01/2014, 07:20

... to Linear Filtering and Prediction Problems. Trans. of the ASME, Series D, Journal of Basic Engineering, 82, pp. 34–45. K ALMAN R.E. and B UCY R.S. (1961) New Results in Linear Filtering ... coefficients with maximum and minimum eigenvalues, λ max and λ min converge according to the following equations: () )(11)( maxmaxmax mv=+mv à (7.96) () )(11)+( minminmin mv=mv à (7.97) ... that for applications in which the LSE is non-zero such as noise reduction, the incremental update term à e ( m ) y ( m ) would remain non-zero even when the optimal point is reached. Thus...

Ngày tải lên: 21/01/2014, 07:20

... Sub-Band Linear Prediction 8.6 Signal Restoration Using Linear Prediction Models 8.7 Summary inear prediction modelling is used in a diverse area of applications, such as data forecasting, ... In linear prediction two coefficients are required for modelling each spectral peak of the signal spectrum. For example, the modelling of a signal with K dominant resonances in the spectrum ... preceding samples. In this section, we study the short-term linear prediction model. In Section 8.3, the predictor model is extended to include long-term pitch period correlations. A linear...

Ngày tải lên: 21/01/2014, 07:20

... acoustic noise emanating from moving, vibrating or colliding sources such as revolving machines, moving vehicles, computer fans, keyboard clicks, wind, rain, etc. to radio-frequency electromagnetic ... coder. 2 NOISE AND DISTORTION 2.1 Introduction 2.6 Thermal Noise 2.2 White Noise 2.7 Shot Noise 2.3 Coloured Noise 2.8 Electromagnetic Noise 2.4 Impulsive Noise 2.9 Channel Distortions ... 2.1 Introduction Noise may be defined as any unwanted signal that interferes with the communication, measurement or processing of an information-bearing signal. Noise is present in various...

Ngày tải lên: 25/01/2014, 13:20

... reviewed in this chapter. Chapter 2 provides an introduction to noise and distortion. Several different types of noise, including thermal noise, shot noise, acoustic noise, electromagnetic noise ... a Noise Pulse Process 384 13.3 Detection of Noise Pulses 385 13.3.1 Matched Filter for Noise Pulse Detection 386 13.3.2 Noise Detection Based on Inverse Filtering 388 13.3.3 Noise Detection ... Impulsive Noise Removal Using Linear Prediction Models 366 12.4.1 Impulsive Noise Detection 367 12.4.2 Analysis of Improvement in Noise Detectability 369 12.4.3 Two-Sided Predictor for Impulsive Noise...

Ngày tải lên: 25/01/2014, 13:20

... A single pulse from the periodic train in (a) with an imagined “ off ” duration of infinity; its spectrum is the envelope of the spectrum of the periodic signal in (a). 288 Power Spectrum ... product of cosines, or sine and cosine, of different frequencies. Orthogonality implies that the sinusoidal basis functions are independent and can be processed independently. For example, in ... without affecting other frequencies, and in sub- band coding different frequency bands are coded independently and allocated different numbers of bits. (ii) Sinusoidal functions are infinitely...

Ngày tải lên: 26/01/2014, 07:20

... vector c. In general, the quality of interpolation depends on the following factors: (a) The signal correlation structure. For deterministic signals such as sine waves, the theoretical interpolation ... illustrated in Figure 10.2. Note that to maintain the real-time duration of the signal the Introduction 301 sampling rate of the interpolated signal x z (m) needs to be increased by a factor ... 10.1 Introduction The objective of interpolation is to obtain a high-fidelity reconstruction of the unknown or the missing samples of a signal. The emphasis in this chapter is on the interpolation...

Ngày tải lên: 26/01/2014, 07:20

... distorting effect of spectral subtraction on the distribution of the signal spectrum. As shown, owing to the noise- induced increase in the variance of the signal spectrum, after subtraction ... SPECTRAL SUBTRACTION 11.1 Spectral Subtraction 11.2 Processing Distortions 11.3 Non-Linear Spectral Subtraction 11.4 Implementation of Spectral Subtraction 11.5 Summary pectral ... correlation of spectral components along the time domain increases with decreasing window length and increasing overlap. However, increasing the overlap can also increase the correlation of noise frequencies...

Ngày tải lên: 26/01/2014, 07:20