Evaluation of Pan-Sharpening Techniques Using Lagrange Optimization

Earth’s observation satellites, such as IKONOS, provide simultaneously multispectral and panchromatic images. A multispectral image comes with a lower spatial and higher spectral resolution in contrast to a panchromatic image which usually has a high spatial and a low spectral resolution. Pan-sharpening represents a fusion of these two complementary images to provide an output image that has both spatial and spectral high resolutions. The objective of this paper is to propose a new method of pan-sharpening based on pixel-level image manipulation and to compare it with several state-of-art pansharpening methods using different evaluation criteria.  The paper presents an image fusion method based on pixel-level optimization using the Lagrange multiplier. Two cases are discussed: (a) the maximization of spectral consistency and (b) the minimization of the variance difference between the original data and the computed data. The paper compares the results of the proposed method with several state-of-the-art pan-sharpening methods. The performance of the pan-sharpening methods is evaluated qualitatively and quantitatively using evaluation criteria, such as the Chi-square test, RMSE, SNR, SD, ERGAS, and RASE. Overall, the proposed method is shown to outperform all the existing methods

Generalized Quadratic Linearization of Machine Models

In the exact linearization of involutive nonlinear system models, the issue of singularity needs to be addressed in practical applications. The approximate linearization technique due to Krener, based on Taylor series expansion, apart from being applicable to noninvolutive systems, allows the singularity issue to be circumvented. But approximate linearization, while removing terms up to certain order, also introduces terms of higher order than those removed into the system. To overcome this problem, in the case of quadratic linearization, a new concept called "generalized quadratic linearization" is introduced in this paper, which seeks to remove quadratic terms without introducing third-and higher-order terms into the system. Also, solution of generalized quadratic linearization of a class of control affine systems is derived. Two machine models are shown to belong to this class and are reduced to only linear terms through coordinate and state feedback. The result is applicable to other machine models as well

Analysis and design of intelligent automation systems

The report details three research projects: performance based automatic control system design, GA based resource allocation methods and statistical image segmentation using MRFs and Reversible jumps.RGM 19/9

Development of automatic testing system for process control instrumentation

In this report, the automated determination of the control valve characteristics using a microcomputer in the laboratory and the autmatic calibration of a differential pressure transmitter using a microcomputer are discussed.RP 33/8

Adaptive tuning and control of process plants using neural networks

A new method of correlating the output variable with the input variables of the system has been used in this project to determine the extent of time delays. The proposed method has an intuitive appeal and is easy to apply. Based on the data obtained for an industrial heater, various series-parallel neural networks of different external configurations are constructed and examined for their capabilities as one-step ahead predictors as well as long term predictors.RP 15/9

Implementation of microprocessor-based digital control strategies on a heat exchanger

A laboratory scale Heat Exchanger unit and its control are described

Microprocessor-based automatic chlorine injection control system for swimming pools

This report describes the development of a cost-effective microprocessor-based digital controller for use with the chlorination systems in small and private swimming pools.RP 13/8

Electronic linesman for tennis tournaments

This report provides a detailed account of the technical alternatives considered as well as the development of the technique finally selected for the application.RP 9/8

Generalized Quadratic Linearization of Machine Models

In the exact linearization of involutive nonlinear system models, the issue of singularity needs to be addressed in practical applications. The approximate linearization technique due to Krener, based on Taylor series expansion, apart from being applicable to noninvolutive systems, allows the singularity issue to be circumvented. But approximate linearization, while removing terms up to certain order, also introduces terms of higher order than those removed into the system. To overcome this problem, in the case of quadratic linearization, a new concept called “generalized quadratic linearization” is introduced in this paper, which seeks to remove quadratic terms without introducing third- and higher-order terms into the system. Also, solution of generalized quadratic linearization of a class of control affine systems is derived. Two machine models are shown to belong to this class and are reduced to only linear terms through coordinate and state feedback. The result is applicable to other machine models as well