Image fusion in GRDSS for Land use Mapping

Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.

Mathematical Analysis of Sensor Fusion for Intrusion Detection Systems

Fusion of multiple intrusion detection systems results in a more reliable and accurate detection for a wider class of intrusions. The paper presented here introduces the mathematical basis for sensor fusion and provides enough support for the acceptability of sensor fusion in performance enhancement of intrusion detection systems. The sensor fusion system is characterized and modeled with no knowledge of the intrusion detection systems and the intrusion detection data. The theoretical analysis is supported with an experimental illustration with three of the available intrusion detection systems using the DARPA 1999 evaluation data set.

Fusion of multi resolution remote sensing data for urban sprawl analysis

Urban population is growing at around 2.3 percent per annum in India. This is leading to urbanisation and often fuelling the dispersed development in the outskirts of urban and village centres with impacts such as loss of agricultural land, open space, and ecologically sensitive habitats. This type of upsurge is very much prevalent and persistent in most places, often inferred as sprawl. The direct implication of such urban sprawl is the change in land use and land cover of the region and lack of basic amenities, since planners are unable to visualise this type of growth patterns. This growth is normally left out in all government surveys (even in national population census), as this cannot be grouped under either urban or rural centre. The investigation of patterns of growth is very crucial from regional planning point of view to provide basic amenities in the region. The growth patterns of urban sprawl can be analysed and understood with the availability of temporal multi-sensor, multi-resolution spatial data. In order to optimise these spectral and spatial resolutions, image fusion techniques are required. This aids in integrating a lower spatial resolution multispectral (MSS) image (for example, IKONOS MSS bands of 4m spatial resolution) with a higher spatial resolution panchromatic (PAN) image (IKONOS PAN band of 1m spatial resolution) based on a simple spectral preservation fusion technique - the Smoothing Filter-based Intensity Modulation (SFIM). Spatial details are modulated to a co-registered lower resolution MSS image without altering its spectral properties and contrast by using a ratio between a higher resolution image and its low pass filtered (smoothing filter) image. The visual evaluation and statistical analysis confirms that SFIM is a superior fusion technique for improving spatial detail of MSS images with the preservation of spectral properties.

Pixel based fusion using IKONOS imagery

Pixel based image fusion entails combining geometric details of a high-resolution Panchromatic (PAN) image and spectral information of a low-resolution Multispectral (MS) image to produce images with highest spatial content while preserving the spectral information. This work reviews and implements six fusion techniques – À Trous algorithm based wavelet transform (ATW), Mulitresolution Analysis based Intensity Modulation, Gram Schmidt fusion, CN Spectral, Luminance Chrominance and High pass fusion (HPF) on IKONOS imagery having 1 m PAN and 4 m MS channels. Comparative performance analysis of techniques by various methods reveals that ATW followed by HPF perform best among all the techniques.

Confinement-deconfinement transition and spin correlations in a generalized Kitaev model

We present a spin model, namely, the Kitaev model augmented by a loop term and perturbed by an Ising Hamiltonian, and show that it exhibits both confinement-deconfinement transitions from spin liquid to antiferromagnetic/spin-chain/ferromagnetic phases and topological quantum phase transitions between gapped and gapless spin-liquid phases. We develop a fermionic resonating-valence-bonds (RVB) mean-field theory to chart out the phase diagram of the model and estimate the stability of its spin-liquid phases, which might be relevant for attempts to realize the model in optical lattices and other spin systems. We present an analytical mean-field theory to study the confinement-deconfinement transition for large coefficient of the loop term and show that this transition is first order within such mean-field analysis in this limit. We also conjecture that in some other regimes, the confinement-deconfinement transitions in the model, predicted to be first order within the mean-field theory, may become second order via a defect condensation mechanism. Finally, we present a general classification of the perturbations to the Kitaev model on the basis of their effect on it's spin correlation functions and derive a necessary and sufficient condition, within the regime of validity of perturbation theory, for the spin correlators to exhibit a long-ranged power-law behavior in the presence of such perturbations. Our results reproduce those of Tikhonov et al. [Phys. Rev. Lett. 106, 067203 (2011)] as a special case.

Analysis of non-uniform waveguide in MZI and optimization of the power confinement in the waveguide

The technological world has attained a new dimension with the advent of miniaturization and a major breakthrough has evolved in the form of moems, technically more advanced than mems. This breakthrough has paved way for the scientists to research and conceive their innovation. This paper presents a mathematical analysis of the wave propagation along the non-uniform waveguide with refractive index varying along the z axis implemented on the cantilever beam of MZI based moem accelerometer. Secondly the studies on the wave bends with minimum power loss focusing on two main aspects of bend angle and curvature angle is also presented.

Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

Confinement and viscoelastic effects on chain closure dynamics

Chemical reactions inside cells are typically subject to the effects both of the cell's confining surfaces and of the viscoelastic behavior of its contents. In this paper, we show how the outcome of one particular reaction of relevance to cellular biochemistry - the diffusion-limited cyclization of long chain polymers - is influenced by such confinement and crowding effects. More specifically, starting from the Rouse model of polymer dynamics, and invoking the Wilemski-Fixman approximation, we determine the scaling relationship between the mean closure time t(c) of a flexible chain (no excluded volume or hydrodynamic interactions) and the length N of its contour under the following separate conditions: (a) confinement of the chain to a sphere of radius d and (b) modulation of its dynamics by colored Gaussian noise. Among other results, we find that in case (a) when d is much smaller than the size of the chain, t(c) similar to Nd-2, and that in case (b), t(c) similar to N-2/(2 (2H)), H being a number between 1/2 and 1 that characterizes the decay of the noise correlations. H is not known a priori, but values of about 0.7 have been used in the successful characterization of protein conformational dynamics. At this value of H (selected for purposes of illustration), t(c) similar to N-3.4, the high scaling exponent reflecting the slow relaxation of the chain in a viscoelastic medium. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4729041]

Tutorial: implementing a pedestrian tracker using inertial sensors

Shoe-mounted inertial sensors offer a convenient way to track pedestrians in situations where other localization systems fail. This tutorial outlines a simple yet effective approach for implementing a reasonably accurate tracker. This Web extra presents the Matlab implementation and a few sample recordings for implementing the pedestrian inertial tracking system using an error-state Kalman filter for zero-velocity updates (ZUPTs) and orientation estimation.

Probing hemoglobin confinement inside submicron silica tubes using synchrotron SAXS and electrochemical response

The configuration of hemoglobin in solution and confined inside silica nanotubes has been studied using synchrotron small angle X-ray scattering and electrochemical activity. Confinement inside submicron tubes of silica aid in preventing protein aggregation, which is vividly observed for unconfined protein in solution. The radius of gyration (R-g) and size polydispersity (p) of confined hemoglobin was found to be lower than that in solution. This was also recently demonstrated in case of confined hemoglobin inside layered polymer capsules. The confined hemoglobin displayed a higher thermal stability with Rg and p showing negligible changes in the temperature range 25-75 degrees C. The differences in configuration between the confined and unconfined protein were reflected in their electrochemical activity. Reversible electrochemical response (from cyclic voltammograms) obtained in case of the confined hemoglobin, in contrary to the observance of only a cathodic response for the unconfined protein, gave direct indication of the differences between the residences of the electroactive heme center in a different orientation compared to that in solution state. The confined Hb showed loss of reversibility only at higher temperatures. The electron transfer coefficient (alpha) and electron transfer rate constant (k(s)) were also different, providing additional evidence regarding structural differences between the unconfined and confined states of hemoglobin. Thus, absence of any adverse effects due to confinement of proteins inside the inorganic matrices such as silica nanotubes opens up new prospects for utilizing inorganic matrices as protein ``encapsulators'', as well as sensors at varying temperatures.

Fusion of algorithms for compressed sensing

For compressed sensing (CS), we develop a new scheme inspired by data fusion principles. In the proposed fusion based scheme, several CS reconstruction algorithms participate and they are executed in parallel, independently. The final estimate of the underlying sparse signal is derived by fusing the estimates obtained from the participating algorithms. We theoretically analyze this fusion based scheme and derive sufficient conditions for achieving a better reconstruction performance than any participating algorithm. Through simulations, we show that the proposed scheme has two specific advantages: 1) it provides good performance in a low dimensional measurement regime, and 2) it can deal with different statistical natures of the underlying sparse signals. The experimental results on real ECG signals shows that the proposed scheme demands fewer CS measurements for an approximate sparse signal reconstruction.