Abstract: Super-resolution is nowadays used for a high-resolution
image produced from several low-resolution noisy frames. In
this work, we consider the problem of high-quality interpolation of a
single noise-free image. Such images may come from different sources,
i.e., they may be frames of videos, individual pictures, etc. On
the other hand, in the encoder we apply a downsampling via
bidimen-sional interpolation of each frame, and in the decoder we
apply a upsampling by which we restore the original size of the
image. If the compression ratio is very high, then we use a
convolutive mask that restores the edges, eliminating the blur.
Finally, both, the encoder and the complete decoder are implemented
on General-Purpose computation on Graphics Processing Units
(GPGPU) cards. In fact, the mentioned mask is coded inside texture
memory of a GPGPU.
Abstract: The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.
Abstract: Mostly the systems are dealing with time varying
signals. The Power efficiency can be achieved by adapting the system
activity according to the input signal variations. In this context
an adaptive rate filtering technique, based on the level crossing sampling
is devised. It adapts the sampling frequency and the filter order
by following the input signal local variations. Thus, it correlates the
processing activity with the signal variations. Interpolation is required
in the proposed technique. A drastic reduction in the interpolation
error is achieved by employing the symmetry during the interpolation
process. Processing error of the proposed technique is
calculated. The computational complexity of the proposed filtering
technique is deduced and compared to the classical one. Results
promise a significant gain of the computational efficiency and hence
of the power consumption.
Abstract: Linear two-point boundary value problems of order
two are solved using cubic trigonometric B-spline interpolation
method (CTBIM). Cubic trigonometric B-spline is a piecewise
function consisting of trigonometric equations. This method is tested
on some problems and the results are compared with cubic B-spline
interpolation method (CBIM) from the literature. CTBIM is found to
approximate the solution slightly more accurately than CBIM if the
problems are trigonometric.
Abstract: This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.
Abstract: A higher order spline interpolated contour obtained
with up-sampling of homogenously distributed coordinates for
segmentation of kidney region in different classes of ultrasound
kidney images has been developed and presented in this paper. The
performance of the proposed method is measured and compared with
modified snake model contour, Markov random field contour and
expert outlined contour. The validation of the method is made in
correspondence with expert outlined contour using maximum coordinate
distance, Hausdorff distance and mean radial distance
metrics. The results obtained reveal that proposed scheme provides
optimum contour that agrees well with expert outlined contour.
Moreover this technique helps to preserve the pixels-of-interest
which in specific defines the functional characteristic of kidney. This
explores various possibilities in implementing computer-aided
diagnosis system exclusively for US kidney images.
Abstract: In this paper an alternative analysis in the time
domain is described and the results of the interpolation process are
presented by means of functions that are based on the rule of
conditional mathematical expectation and the covariance function. A
comparison between the interpolation error caused by low order
filters and the classic sinc(t) truncated function is also presented.
When fewer samples are used, low-order filters have less error. If the
number of samples increases, the sinc(t) type functions are a better
alternative. Generally speaking there is an optimal filter for each
input signal which depends on the filter length and covariance
function of the signal. A novel scheme of work for adaptive
interpolation filters is also presented.
Abstract: This paper present a new way to find the aerodynamic characteristic equation of missile for the numerical trajectories prediction more accurate. The goal is to obtain the polynomial equation based on two missile characteristic parameters, angle of attack (α ) and flight speed (╬¢ ). First, the understudied missile is modeled and used for flow computational model to compute aerodynamic force and moment. Assume that performance range of understudied missile where range -10< α
Abstract: Natural convection heat transfer from a heated
horizontal semi-circular cylinder (flat surface upward) has been
investigated for the following ranges of conditions; Grashof number,
and Prandtl number. The governing partial differential equations
(continuity, Navier-Stokes and energy equations) have been solved
numerically using a finite volume formulation. In addition, the role of
the type of the thermal boundary condition imposed at cylinder
surface, namely, constant wall temperature (CWT) and constant heat
flux (CHF) are explored. Natural convection heat transfer from a
heated horizontal semi-circular cylinder (flat surface upward) has
been investigated for the following ranges of conditions; Grashof
number, and Prandtl number, . The governing partial differential
equations (continuity, Navier-Stokes and energy equations) have
been solved numerically using a finite volume formulation. In
addition, the role of the type of the thermal boundary condition
imposed at cylinder surface, namely, constant wall temperature
(CWT) and constant heat flux (CHF) are explored. The resulting flow
and temperature fields are visualized in terms of the streamline and
isotherm patterns in the proximity of the cylinder. The flow remains
attached to the cylinder surface over the range of conditions spanned
here except that for and ; at these conditions, a separated flow
region is observed when the condition of the constant wall
temperature is prescribed on the surface of the cylinder. The heat
transfer characteristics are analyzed in terms of the local and average
Nusselt numbers. The maximum value of the local Nusselt number
always occurs at the corner points whereas it is found to be minimum
at the rear stagnation point on the flat surface. Overall, the average
Nusselt number increases with Grashof number and/ or Prandtl
number in accordance with the scaling considerations. The numerical
results are used to develop simple correlations as functions of
Grashof and Prandtl number thereby enabling the interpolation of the
present numerical results for the intermediate values of the Prandtl or
Grashof numbers for both thermal boundary conditions.
Abstract: This paper presents a sensing system for 3D sensing
and mapping by a tracked mobile robot with an arm-type sensor
movable unit and a laser range finder (LRF). The arm-type sensor
movable unit is mounted on the robot and the LRF is installed at the
end of the unit. This system enables the sensor to change position and
orientation so that it avoids occlusions according to terrain by this
mechanism. This sensing system is also able to change the height of
the LRF by keeping its orientation flat for efficient sensing. In this kind
of mapping, it may be difficult for moving robot to apply mapping
algorithms such as the iterative closest point (ICP) because sets of the
2D data at each sensor height may be distant in a common surface. In
order for this kind of mapping, the authors therefore applied
interpolation to generate plausible model data for ICP. The results of
several experiments provided validity of these kinds of sensing and
mapping in this sensing system.
Abstract: For about two decades scientists have been
developing techniques for enhancing the quality of medical images
using Fourier transform, DWT (Discrete wavelet transform),PDE
model etc., Gabor wavelet on hexagonal sampled grid of the images
is proposed in this work. This method has optimal approximation
theoretic performances, for a good quality image. The computational
cost is considerably low when compared to similar processing in the
rectangular domain. As X-ray images contain light scattered pixels,
instead of unique sigma, the parameter sigma of 0.5 to 3 is found to
satisfy most of the image interpolation requirements in terms of high
Peak Signal-to-Noise Ratio (PSNR) , lower Mean Squared Error
(MSE) and better image quality by adopting windowing technique.
Abstract: This paper study the high-level modelling and design
of delta-sigma (ΔΣ) noise shapers for audio Digital-to-Analog
Converter (DAC) so as to eliminate the in-band Signal-to-Noise-
Ratio (SNR) degradation that accompany one channel mismatch in
audio signal. The converter combines a cascaded digital signal
interpolation, a noise-shaping single loop delta-sigma modulator with
a 5-bit quantizer resolution in the final stage. To reduce sensitivity of
Digital-to-Analog Converter (DAC) nonlinearities of the last stage, a
high pass second order Data Weighted Averaging (R2DWA) is
introduced. This paper presents a MATLAB description modelling
approach of the proposed DAC architecture with low distortion and
swing suppression integrator designs. The ΔΣ Modulator design can
be configured as a 3rd-order and allows 24-bit PCM at sampling rate
of 64 kHz for Digital Video Disc (DVD) audio application. The
modeling approach provides 139.38 dB of dynamic range for a 32
kHz signal band at -1.6 dBFS input signal level.
Abstract: Artifact is one of the most important factors in
degrading the CT image quality and plays an important role in
diagnostic accuracy. In this paper, some artifacts typically appear in
Spiral CT are introduced. The different factors such as patient,
equipment and interpolation algorithm which cause the artifacts are
discussed and new developments and image processing algorithms to
prevent or reduce them are presented.
Abstract: in this paper, we propose a numerical method
for the approximate solution of fuzzy Fredholm functional
integral equations of the second kind by using an iterative
interpolation. For this purpose, we convert the linear fuzzy
Fredholm integral equations to a crisp linear system of integral
equations. The proposed method is illustrated by some fuzzy
integral equations in numerical examples.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (''jaggies'') along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first and second order directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: Suppose KY and KX are large sets of observed and
reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori
information only on few signals, p N, from KX but performs better than the known filters based on a priori information on every
reference signal from KX? It is shown that the positive answer is
achievable under quite unrestrictive assumptions. The device behind
the proposed method is based on a special extension of the piecewise
linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from
the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.
Abstract: The purpose of this paper primarily intends to develop GIS interface for estimating sequences of stream-flows at ungauged stations based on known flows at gauged stations. The integrated GIS interface is composed of three major steps. The first, precipitation characteristics using statistical analysis is the procedure for making multiple linear regression equation to get the long term mean daily flow at ungauged stations. The independent variables in regression equation are mean daily flow and drainage area. Traditionally, mean flow data are generated by using Thissen polygon method. However, method for obtaining mean flow data can be selected by user such as Kriging, IDW (Inverse Distance Weighted), Spline methods as well as other traditional methods. At the second, flow duration curve (FDC) is computing at unguaged station by FDCs in gauged stations. Finally, the mean annual daily flow is computed by spatial interpolation algorithm. The third step is to obtain watershed/topographic characteristics. They are the most important factors which govern stream-flows. In summary, the simulated daily flow time series are compared with observed times series. The results using integrated GIS interface are closely similar and are well fitted each other. Also, the relationship between the topographic/watershed characteristics and stream flow time series is highly correlated.
Abstract: Computer based geostatistical methods can offer effective data analysis possibilities for agricultural areas by using
vectorial data and their objective informations. These methods will help to detect the spatial changes on different locations of the large
agricultural lands, which will lead to effective fertilization for optimal yield with reduced environmental pollution. In this study, topsoil (0-20 cm) and subsoil (20-40 cm) samples were taken from a
sugar beet field by 20 x 20 m grids. Plant samples were also collected
from the same plots. Some physical and chemical analyses for these
samples were made by routine methods. According to derived variation coefficients, topsoil organic matter (OM) distribution was more than subsoil OM distribution. The highest C.V. value of
17.79% was found for topsoil OM. The data were analyzed
comparatively according to kriging methods which are also used
widely in geostatistic. Several interpolation methods (Ordinary,Simple and Universal) and semivariogram models (Spherical,
Exponential and Gaussian) were tested in order to choose the suitable
methods. Average standard deviations of values estimated by simple
kriging interpolation method were less than average standard
deviations (topsoil OM ± 0.48, N ± 0.37, subsoil OM ± 0.18) of measured values. The most suitable interpolation method was simple
kriging method and exponantial semivariogram model for topsoil,
whereas the best optimal interpolation method was simple kriging
method and spherical semivariogram model for subsoil. The results
also showed that these computer based geostatistical methods should
be tested and calibrated for different experimental conditions and semivariogram models.
Abstract: This paper proposes fractal patterns for power quality
(PQ) detection using color relational analysis (CRA) based classifier.
Iterated function system (IFS) uses the non-linear interpolation in the
map and uses similarity maps to construct various fractal patterns of
power quality disturbances, including harmonics, voltage sag, voltage
swell, voltage sag involving harmonics, voltage swell involving
harmonics, and voltage interruption. The non-linear interpolation
functions (NIFs) with fractal dimension (FD) make fractal patterns
more distinguishing between normal and abnormal voltage signals.
The classifier based on CRA discriminates the disturbance events in a
power system. Compared with the wavelet neural networks, the test
results will show accurate discrimination, good robustness, and faster
processing time for detecting disturbing events.
Abstract: This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.