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Simulations of the adaptive reconstruction have been performed for a single slice of a porosity in ferritic weld as shown in Fig. 2a [11]. The image matrix has the dimensions 230x120 pixels. The number of beams in each projection is M=131. The total number of projections K was chosen to be 50. For the projections the usual CT setup was used restricted to angels between 0° and 180° with the uniform step size of about 3.7°. The diagonal form of the quadratic criteria F(a,a) and f(a,a) were used for the reconstruction algorithms (5) and (6). [Pg.124]

In many cases, the methods used to solve identification problems are based on an iterative minimization of some performance criterion measuring the dissimilarity between the experimental and the synthetic data (generated by the current estimate of the direct model). In our case, direct quantitative comparison of two Bscan images at the pixels level is a very difficult task and involves the solution of a very difficult optimization problem, which can be also ill-behaved. Moreover, it would lead to a tremendous amount of computational burden. Segmented Bscan images may be used as concentrated representations of the useful... [Pg.172]

Information of the energy imparted to the entrance screen is then transferred through a number of conversions in the detector chain, which introduce pixel-to-pixel correlation, before it is stored as digital data. This correlation has to be considered to be able to predict absolute signal and noise levels in the stored, data the noise would otherwise be overestimated. [Pg.211]

FbwO) is the Fourier transformation of effective beam width as a function of spatial frequency / Fuff) is the MTF of the XRll. Because of the XRll windows curvature, projection data must be transformed to obtain uniform pixel spacing, described by Errors in object centre... [Pg.212]

The function / represents the pixel s intensity and takes its values in the discrete E of K elements ... [Pg.232]

The Co-Occurrence Matrix is a function of two variables i and j, the intensities of two pixels, each in E it takes its elements in N (set of natural integers). [Pg.232]

The parameters of this matrix are the image / and the vector d written by [dx, dy] in cartesian coordinates or [ r, 0] in polar coordinates. The number of co-occurrence on the image / of pairs of pixels separated by vector d. The latter pairs have i and j intensities respectively, i.e. [Pg.232]

For an operation of seginentation, the vector d will have to be calculated that matrix allows to separate the noise of defects. We search transitions of frontiers, there is all couples (i, j) of pixels such that i is an intensity linked to the noise and j an intensity linked to the defect. [Pg.233]

Back-ground / Object Edges. A couple of pixels is included in the border between an object and the bottom of the image if one of pixels belongs to the object and the other to the bottom, one can therefore define the border as the totality of pixels of the object that belong to a couple of pixels linked to the main issue. The size of tliis totality corresponds to the number of couples of pixels included in the border and depends on the option of the vector d. [Pg.234]

A couple of pixels is included in the frontier between an object and the background of the image, if one of pixels belongs to the object and the other to the background. [Pg.234]

For our ultrasonic images, pixels belonging to the vertical axis ate separated by the displacement px of the translator, while on the horizontal axis, pixels are separated by a period of sampling. [Pg.234]

It represents the average distance to the barycentre of the block B3 and reach its maximum when pixels are distanced the barycentre. [Pg.236]

If in the section defects are absent, the projections is distributed accidentally on pixels and the values of functions p(ij) aproximately are alike in all pixels of the section. In defective areas the projections are focused and, as far as defect appearance is unlikely on accepted hypothesis... [Pg.249]

On the base of functions g CO by splitting of the NDTO volume on pixels and typical sections... [Pg.251]

Approach to restoring of stresses SD in the three-dimensional event requires for each pixel determinations of matrix with six independent elements. Type of matrixes depends on chosen coordinate systems. It is arised a question, how to present such result for operator that he shall be able to value stresses and their SD. One of the possible ways is a calculation and a presenting in the form of image of SD of stresses tensor invariants. For three-dimensional SDS relative increase of time of spreading of US waves, polarized in directions of main axises of stresses tensor ... [Pg.252]

Secondly, the linearized inverse problem is, as well as known, ill-posed because it involves the solution of a Fredholm integral equation of the first kind. The solution must be regularized to yield a stable and physically plausible solution. In this apphcation, the classical smoothness constraint on the solution [8], does not allow to recover the discontinuities of the original object function. In our case, we have considered notches at the smface of the half-space conductive media. So, notche shapes involve abrupt contours. This strong local correlation between pixels in each layer of the half conductive media suggests to represent the contrast function (the object function) by a piecewise continuous function. According to previous works that we have aheady presented [14], we 2584... [Pg.326]

The a priori information involved by this modified Beta law (5) does not consider the local correlation between pixels, however, the image f is mainly constituted from locally constant patches. Therefore, this a priori knowledge can be introduced by means of a piecewise continuous function, the weak membrane [2]. The energy related to this a priori model is ... [Pg.331]

The pixel resolution is 50 pm or 25 pm. Unfortunately (from the point of NDT), the max. IP-size is limited to 20 x 25 cm. The max. image size amounts to 160 MByte. Both systems are equipped with new types of IP s. [Pg.469]

During the calibration the geometric distortions in the images are reduced from a maximum of more than 11 pixels to less than 0.3 pixels (pixel size about 0.28mm 0.28mm). The whole calibration results in a maximum deviation of the projected calibration marks from the measured calibration marks in the image of less than 0.4 pixel (2D-error). [Pg.490]

The detector setup consists of four 256 x 256 pixel amorphous silicon technology sensor flat panels with 0.75 x 0.75 mm pixel size, having an active area of 192 x 192 mm [5j. These sensors are radiation sensitive up to 25 MeV and therefor well suited for detecting the LINAC radiation. The four devices are mounted onto a steel Irame each having the distance of one active area size from the other. With two vertical and two horizontal movements of the frame it is possible to scan a total area of about 0.8 x 0.8 m with 1024 x 1024 pixel during four independent measurements. [Pg.493]


See other pages where Pixels is mentioned: [Pg.113]    [Pg.113]    [Pg.115]    [Pg.124]    [Pg.125]    [Pg.173]    [Pg.203]    [Pg.209]    [Pg.210]    [Pg.211]    [Pg.211]    [Pg.211]    [Pg.212]    [Pg.234]    [Pg.249]    [Pg.249]    [Pg.249]    [Pg.251]    [Pg.252]    [Pg.327]    [Pg.331]    [Pg.332]    [Pg.401]    [Pg.444]    [Pg.459]    [Pg.469]    [Pg.472]    [Pg.478]    [Pg.484]    [Pg.487]    [Pg.498]   
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Active matrix LCDs pixel

Active matrix organic light-emitting diode pixel

Active pixel sensor

Actuator pixel

Analysis of crystal polymorphism by Pixel and quantum chemical calculations

Background correction pixel

Border pixels

Complex Pixel Design

Construction and Commissioning of the CMS Pixel Barrel Detector

Current-programmed pixels

Defective pixel

Design of the CMS Pixel Barrel Detector

Detector characteristics pixel sizes

Detector multi-pixel

Detector pixel width

Digital image pixel size

Distance between pixels

Full density models the SCDS-Pixel method

Hybrid Pixel Arrays with Data Push Architecture

Hybrid pixel detectors

Liquid crystal displays, LCDs pixels

Local rank pixel

Measurement pixel

Monolithic Pixel Arrays

PIXEL method

Photographic pixel

Pixel AMLCD

Pixel AMOLED

Pixel Detector Option

Pixel anomalous

Pixel area

Pixel binning

Pixel capacitance

Pixel characteristics

Pixel characteristics characteristic

Pixel circuits designs

Pixel clock

Pixel compression

Pixel densities, image analysis

Pixel design, optimal

Pixel errors

Pixel images

Pixel inversion

Pixel maps

Pixel method parameters

Pixel rate

Pixel resolution

Pixel response

Pixel size

Pixel subpixel

Pixel switching

Pixel voltage-programmed

Pixel width

Pixel, definition

Pixel, pixels

Pixel, pixels

Pixelated scintilator

Pixels active matrix displays

Pixels displays

Pixels over-illumination

Pixels smart

Pixels super

Pixels, OLED

Pixels, Patterning, and Drivers

Pixels, atomic spectroscopy

Pixels: charge-coupled devices

Pixels: charge-coupled devices defined

Polarizers/Polarization pixelated polarizer

Reference pixel

Semi-classical Approaches the SCDS-Pixel Method

Side pixel registration

Silicon Pixel Devices

Spatial frequency pixels

Stimulator pixels

TFT Pixel Design Considerations

The Voltage Programming Pixel Circuit

Volume pixels

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