Department of Mathematics

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IIT Jodhpur

Multi-modal medical image fusion, as a powerful tool for the clinical applications, has developed with the advent of various imaging modalities in medical imaging. The main motivation is to capture most relevant information from sources into a single output, which plays an important role in medical diagnosis. In this paper, a novel framework for medical image fusion based on framelet transform is proposed considering the characteristics of human visual system (HVS). The core idea behind the proposed framework is to decompose all source images by the framelet transform. Two different HVS inspired fusion rules are proposed for combining the low- and high-frequency coefficients respectively. The former is based on the visibility measure, and the latter is based on the texture information. Finally, the fused image is constructed by the inverse framelet transform with all composite coefficients. Experimental results highlight the expediency and suitability of the proposed framework. The efficiency of the proposed method is demonstrated by the different experiments on different multi-modal medical images. Further, the enhanced performance of the proposed framework is understood from the comparison with existing algorithms. © 2012 Elsevier Ltd. All rights reserved.

World University root node

Expert Systems with Applications

Human visual system inspired multi-modal medical image fusion framework

The main objective of this paper is to perform data analysis of ground based measurement and review the state of the art of IIT Jodhpur Rooftop solar photovoltaic installed 101 kW system. Solar power forecasting is playing a key role in solar PV park installation, operation and accurate solar power dispatchability as well as scheduling. Solar Power varies with time and geographical locations and meteorological conditions such as ambient temperature, wind velocity, solar radiation and module temperature. The location of Solar PV system is the main reason of solar power variability. Solar variability totally depends on system losses (deterministic losses) and weather parameter (stochastic losses). In the case of solar power, deterministic losses can be found out accurately but stochastic losses are very uncertain and unpredicted in nature. The proposed soft computing technique will be suitable for solar power forecasting modeling. In this paper Fuzzy theory, Adaptive Neuro-fuzzy interface system, artificial neural network and generalized neural network are used as powerful tool of solar power Forecasting. This soft computing cum nature inspired techniques are able to accurately and fast forecasting compared to conventional methods of forecasting. This is done analyzing the operational data of 101 kW PV systems (43.30 kW located in Block 1 and 58.08 kW in Block 2), during the year 2011. © 2013 IEEE.

2013 13th International Conference on Environment and Electrical Engineering, EEEIC 2013 - Conference Proceedings

Generalized neural network methodology for short term solar power forecasting

In this paper, a small novel octagonal shaped ultra wideband (UWB) antenna was designed using Minkowski like fractal geometry including the multi band notch characteristics. The investigated UWB antenna geometry addresses the challenges such as compact size and wideband operating frequency range because of the self-similar and multiple resonance characteristics of the fractal geometry, used in this work. The multiple notches in the ground plane leads to better return loss and the desired operational bandwidth in the 3.1 GHz - 10.6 GHz range. The compact 16.5 mm × 13.5 mm antenna geometry exhibits nearly omnidirectional radiation pattern, proper impedance matching with VSWR &lt; 2 over the entire UWB frequency range. These characteristics offer opportunities to explore the proposed UWB antenna for various applications. © 2013 IEEE.

Department of Physics

2013 International Conference on Signal Processing and Communication, ICSC 2013

A novel multi band notched octagonal shaped fractal UWB antenna

Multifocus image fusion is the process of obtaining a single image from multiple partially focused images such that the newly formed image consists of the well-defined information extracted from each source image. This paper proposes the use of saliency of the source images based on Mutual Spectral Residual. Spectral Residual brings out the unique/salient features of an image in frequency domain. The idea of proposed mutual spectral residual is to emphasize the relative unique features of a source image with respect to the other source images. The relative unique features are utilized to form saliency maps for each source image. These saliency maps can clearly indicate the focused and defocused parts of an image. Based on the saliency maps obtained, the image fusion takes place in spatial domain. Visual inspection and quantitative evaluation of the fused images obtained by the proposed method, using different evaluation metrics, demonstrate its effectiveness over several existing image fusion methods. © 2013 Elsevier Inc. All rights reserved.

Digital Signal Processing: A Review Journal

Mutual spectral residual approach for multifocus image fusion

In this paper, a new watermarking scheme based on redundant fractional wavelet transform is presented. First, the definition and implementation of redundant fractional wavelet transform is proposed followed by its use in watermark embedding. For embedding, the gray-scale logo watermark is used and is embedded in the middle singular values of the redundant fractional wavelet domain. In order to enhance the security, a binary watermark is also embedded in the host image in lossless manner based on automatic thresholding. Finally, a reliable extraction process is developed for the extraction of both the watermarks from the possibly distorted image. The feasibility and robustness of the proposed technique is carried out by the security and attack analysis on different images. © 2013.

Fulltext

Mathematical and Computer Modelling

A new logo watermarking based on redundant fractional wavelet transform

The fractional wavelet transform is a useful mathematical transformation that generalizes the most prominent tool in signal and image processing namely wavelet transform by rotation of signals in the time-frequency plane. The definition of discrete fractional wavelet transform is not reported yet in the literature. Therefore, a definition of the discrete fractional wavelet transform is consolidated by discretizing continuous fractional wavelet transform in the proposed work. Possible applications of the transform are in transient signal processing, image analysis, image transmission, biometrics, image compression etc. In this paper, image transmission is chosen as the primary application and hence a novel encryption scheme is proposed for securing multiple images during communication and transmission over insecure channel. The proposed multiple image encryption scheme is consolidated by fractional wavelet transform and chaotic maps. First, all the images are encrypted followed by their sharing. The sharing process is done considering numerical techniques by making the sharing process a system of linear equations. Experimental results and security analysis demonstrate the efficiency and robustness of the proposed primary application. © 2012 Elsevier Inc. All rights reserved.

Information Sciences

Discrete fractional wavelet transform and its application to multiple encryption

In this paper, a novel biometrics inspired watermarking technique is proposed. For this purpose, a newly proposed mathematical transform, namely the fractional dual tree complex wavelet transform (FrDT-CWT), and singular value decomposition (SVD) are used. The core idea is to use biometrically generated keys in the embedding process of a gray-scale watermark. Therefore, this paper first proposes a method for generating keys from biometrics efficiently. The host image is first randomized by Hessenberg decomposition and a chaotic map, followed by embedding in the FrDT-CWT domain by modifying the singular values of the randomized image. Further, in order to prevent the ambiguity problem of SVD-based techniques, a verification step is introduced to verify the watermarked image. Finally, a reliable extraction process is proposed to extract the watermark from the possibly attacked watermarked image after verification. The security, attack, and comparative analysis confirms the high security, efficiency, and robustness of the proposed watermarking technique. © 2012 Elsevier B.V. All rights reserved.

Future Generation Computer Systems

Biometrics inspired watermarking based on a fractional dual tree complex wavelet transform

Let g0 denote the standard metric on S4 and Pg0=δg02-2δg0 denote the corresponding Paneitz operator. In this work, we study the following fourth order elliptic problem with exponential nonlinearityPg0u+6=2Q(x)e4uon S4. Here Q is a prescribed smooth function on S4 which is assumed to be a perturbation of a constant. We prove existence results to the above problem under assumptions only on the "shape" of Q near its critical points. These are more general than the non-degeneracy conditions assumed so far. We also show local uniqueness and exact multiplicity results for this problem. The main tool used is the Lyapunov-Schmidt reduction. © 2013.

Journal of Differential Equations

On the perturbed Q-curvature problem on S4

Optimum lifetime of a series system with active spares always depends on the allocation of spares at component /system level. We prove that under some sufficient conditions, component redundancy offers greater reliability than the system redundancy in likelihood ratio ordering for n-component matching spares. We also show that this principle holds under some sufficient conditions in likelihood ratio ordering for 2-component non-matching spares of iid components and iid spares. Further, we give some sufficient conditions under which reversed hazard rate order does not exist between two 2-component systems of matching spares. © 2013 Elsevier B.V. All rights reserved.

Operations Research Letters

Some results on active redundancy at component level versus system level

Joint watermarking and encryption is an upcoming security solution that combines leading but complementary techniques to achieve an enhanced security level. Real time applications using joint watermarking and encryption framework has three requirements: data to be efficiently compressed, watermarking technique to sustain compression, and encryption technique to be developed in a way so as not to disturb the compression efficiency. Finding an optimal solution that combines the three techniques while fulfilling these requirements is a challenging problem. This paper thus, proposes a wavelet domain based joint watermarking and encryption framework that employs singular value decomposition based watermark embedding and sign bit encryption prior to compression. The varying significance of different subbands has been considered to encrypt the data without adversely effecting the compression ratio. Experimental analysis using various evaluation parameters and attack scenarios has revealed the ability of the proposed framework to prove content-ownership, even from the encrypted data. Comparative analysis with the existing techniques reflect its ability to provide better security with less computational resources. This makes it a preferable solution for data security at all stages of data archival, transmission or distribution. © 2012 Springer Science+Business Media, LLC.