1,028 research outputs found
A New Class of Monotone/Convex Rational Fractal Function
This paper presents a description and analysis of a rational cubic spline FIF
(RCSFIF) that has two shape parameters in each subinterval when it is defined
implicitly. To be precise, we consider the iterated function system (IFS) with
, , where are cubic
polynomials to be determined through interpolatory conditions of the
corresponding FIF and are preassigned quadratic polynomials each
containing two free shape/rationality parameters. We establish the convergence
of the proposed RCSFIF to the original function
with respect to the uniform norm. We also provide the sufficient conditions for
an automatic selection of the rational IFS parameters to preserve monotonicity
and convexity of a prescribed set of data points. We consider some examples to
illustrate the developed fractal interpolation scheme and its shape preserving
aspects.Comment: 18 Pages, 18 Figures. arXiv admin note: text overlap with
arXiv:1809.0820
An evolutionary computational based approach towards automatic image registration
Image registration is a key component of various image processing operations
which involve the analysis of different image data sets. Automatic image
registration domains have witnessed the application of many intelligent
methodologies over the past decade; however inability to properly model object
shape as well as contextual information had limited the attainable accuracy. In
this paper, we propose a framework for accurate feature shape modeling and
adaptive resampling using advanced techniques such as Vector Machines, Cellular
Neural Network (CNN), SIFT, coreset, and Cellular Automata. CNN has found to be
effective in improving feature matching as well as resampling stages of
registration and complexity of the approach has been considerably reduced using
corset optimization The salient features of this work are cellular neural
network approach based SIFT feature point optimisation, adaptive resampling and
intelligent object modelling. Developed methodology has been compared with
contemporary methods using different statistical measures. Investigations over
various satellite images revealed that considerable success was achieved with
the approach. System has dynamically used spectral and spatial information for
representing contextual knowledge using CNN-prolog approach. Methodology also
illustrated to be effective in providing intelligent interpretation and
adaptive resampling.Comment: arXiv admin note: substantial text overlap with arXiv:1303.671
An N-dimensional approach towards object based classification of remotely sensed imagery
Remote sensing techniques are widely used for land cover classification and
urban analysis. The availability of high resolution remote sensing imagery
limits the level of classification accuracy attainable from pixel-based
approach. In this paper object-based classification scheme based on a
hierarchical support vector machine is introduced. By combining spatial and
spectral information, the amount of overlap between classes can be decreased;
thereby yielding higher classification accuracy and more accurate land cover
maps. We have adopted certain automatic approaches based on the advanced
techniques as Cellular automata and Genetic Algorithm for kernel and tuning
parameter selection. Performance evaluation of the proposed methodology in
comparison with the existing approaches is performed with reference to the
Bhopal city study area
A review over the applicability of image entropy in analyses of remote sensing datasets
Entropy is the measure of uncertainty in any data and is adopted for
maximisation of mutual information in many remote sensing operations. The
availability of wide entropy variations motivated us for an investigation over
the suitability preference of these versions to specific operations.Comment: arXiv admin note: substantial text overlap with arXiv:1303.692
Cellular Automata based adaptive resampling technique for the processing of remotely sensed imagery
Resampling techniques are being widely used at different stages of satellite
image processing. The existing methodologies cannot perfectly recover features
from a completely under sampled image and hence an intelligent adaptive
resampling methodology is required. We address these issues and adopt an error
metric from the available literature to define interpolation quality. We also
propose a new resampling scheme that adapts itself with regard to the pixel and
texture variation in the image. The proposed CNN based hybrid method has been
found to perform better than the existing methods as it adapts itself with
reference to the image features
An investigation towards wavelet based optimization of automatic image registration techniques
Image registration is the process of transforming different sets of data into
one coordinate system and is required for various remote sensing applications
like change detection, image fusion, and other related areas. The effect of
increased relief displacement, requirement of more control points, and
increased data volume are the challenges associated with the registration of
high resolution image data. The objective of this research work is to study the
most efficient techniques and to investigate the extent of improvement
achievable by enhancing them with Wavelet transform. The SIFT feature based
method uses the Eigen value for extracting thousands of key points based on
scale invariant features and these feature points when further enhanced by the
wavelet transform yields the best results
A Comparative Analysis on the Applicability of Entropy in remote sensing
Entropy is the measure of uncertainty in any data and is adopted for
maximisation of mutual information in many remote sensing operations. The
availability of wide entropy variations motivated us for an investigation over
the suitability preference of these versions to specific operations.
Methodologies were implemented in Matlab and were enhanced with entropy
variations. Evaluation of various implementations was based on different
statistical parameters with reference to the study area The popular available
versions like Tsalli's, Shanon's, and Renyi's entropies were analysed in
context of various remote sensing operations namely thresholding, clustering
and registration
Parameter Identification of Constrained Data by a New Class of Rational Fractal Function
This paper sets a theoretical foundation for the applications of the fractal
interpolation functions (FIFs). We construct rational cubic spline FIFs
(RCSFIFs) with quadratic denominator involving two shape parameters. The
elements of the iterated function system (IFS) in each subinterval are
identified befittingly so that the graph of the resulting
-RCSFIF lies within a prescribed rectangle. These parameters
include, in particular, conditions on the positivity of the
-RCSFIF. The problem of visualization of constrained data is
also addressed when the data is lying above a straight line, the proposed
fractal curve is required to lie on the same side of the line. We illustrate
our interpolation scheme with some numerical examplesComment: 16 pages, 9 Figures. Presented by Sangita Jha at International
Conference on Mathematics and Computing, Haldia, January 17-21, 201
Bicubic partially blended rational quartic surface
This paper investigates some univariate and bivariate constrained
interpolation problems using rational quartic fractal interpolation functions,
which has been submitted long back in a reputed journal and revised as per the
journal requirement. This research is extension of the work [S. K. Katiyar and
A. K. B. Chand, Shape Preserving Rational Quartic Fractal Functions, Fractal,
in Press]
One-magnon (electromagnon) light scattering in BiFeO3 single crystals
We observed Raman scattering from magnon in frequency range from 10 to 65
cm-1 in BiFeO3 single crystals at cryogenic temperatures; the temperature
dependence of the magnon frequency at 18.2 cm-1 approximates an S=5/2 Brillouin
function up to the temperature (280 K) at which the magnon becomes overdamped.
The diverging cross-section and the frequency-shift at 140K and 200 K implies a
magnon-reorientation transition as in orthoferrites. Magnons in polar materials
such as BiFeO3 are often termed electromagnons meaning that they possess an
electric dipole moment due to magnetoelectric coupling.Comment: 6 pages, 4 figure
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