FUSION OF HYPERSPECTRAL AND MULTISPECTRAL IMAGERY WITH REGRESSION KRIGING AND THE LULU OPERATORS; A COMPARISON

In this digital world, there is a large requirement of high resolution satellite image. Images at a low resolution may contain relevant information that has to be integrated with the high resolution image to obtain the required information. This is being fulfilled by image fusion. Image fusion is merging of different resolution images into a single image. The output image contains more information, as the information is integrated from both the images Image fusion was conducted with two different algorithms: regression kriging and the LULU operators. First, regression Kriging estimates the value of a dependent variable at unsampled location with the help of auxiliary variables. Here we used regression Kriging with the Hyperion image band as the response variables and the LISS III image bands are the explanatory variables. The fused image thus has the spectral variables from Hyperion image and the spatial variables from the LISS III image. Second, the LULU operator is an image processing methods that can be used as well in image fusion technique. Here we explored to fuse the Hyperion and LISS III image. The LULU operators work in three stages of the process, viz the decomposition stage, the fusion and the reconstruction stage. Quality aspects of the fused image for both techniques have been compared for spectral quality (correlation) and spatial quality (entropy). The study concludes that the quality of the fused image obtained with regression kriging is better than that obtained with the LULU operator

Bayesian Inference in Exponential and Pareto populations in the presence of Outliers

This thesis Entitled Bayesian inference in Exponential and pareto populations in the presence of outliers. The main theme of the present thesis is focussed on various estimation problems using the Bayesian appraoch, falling under the general category of accommodation procedures for analysing Pareto data containing outlier. In Chapter II. the problem of estimation of parameters in the classical Pareto distribution specified by the density function. In Chapter IV. we discuss the estimation of (1.19) when the sample contain a known number of outliers under three different data generating mechanisms, viz. the exchangeable model. Chapter V the prediction of a future observation based on a random sample that contains one contaminant. Chapter VI is devoted to the study of estimation problems concerning the exponential parameters under a k-outlier model.Cochin University of Science and TechnoloyDepartment of Mathematics and Statistics, Cochin University of Science and Technolo

Prediction of future observations from Pareto population in the presence of an outlier

In this article a method of calculating prediction intervals for the order statistics from the Pareto population based on samples which contain a discordant observation is presented

Facial talon cusp: A rarity, report of a case with one year follow up and flashback on reported cases

Talon cusp is a relatively uncommon developmental anomaly characterized by cusp-like projections, usually presenting on palatal/lingual surface of the anterior teeth. This cusp resembles an eagle's talon, and hence the name. Normal enamel and dentin covers the cusp, which may or may not contain an extension of pulp. Presence of this anomalous cusp on the facial surface of an anterior tooth is a rare finding and very few cases have been reported in the literature. In most instances, such cusps are associated with clinical problems such as poor esthetics and caries susceptibility. Management of such cases requires a comprehensive knowledge of the clinical entity as well as the problems associated with it. This case report presents a facial talon cusp on the maxillary left central incisor of a 10 year old boy, which was conservatively treated. Vitality of the affected tooth was maintained and followed up for a period of 1 year

Developing Genetic Coefficients of Sorghum Cultivars Using Gencalc and Glue Genetic Coefficient Estimators in DSSAT

DSSAT (Decision Support System for Agrotechnology Transfer) is a software system used for crop growth and development, soil and water balance, nutrient cycling, climate change impact simulations and precision agriculture. The objective of this study was to calibrate and validate the sorghum cultivars TNAU sorghum CO 30 and K12 under various sowing windows and fertilizer applications. CERES-Sorghum model (DSSAT v 4.7.5) was calibrated and validated using experimental field data obtained from Tamil Nadu Agricultural University, Coimbatore. The  derived  genotype  co-efficients  of  sorghum cultivars simulated the phenology, growth and yield accurately well under various sowing windows  and  nitrogen  levels. The nRMSE (Normalised Root Mean Square Error) values for simulations for grain yield were 2.4 per cent and 8.8 per cent for TNAU sorghum CO 30 and K12, respectively. The mean simulated grain yield was 3127 kg/ha against the observed grain yield of 3052 kg/ha in TNAU CO 30 sorghum. The mean observed grain yield was 3312 kg/ha against the observed grain yield of 3020 kg/ha K 12. The model satisfactorily simulated the phenology and yield of sorghum cultivars, and hence it can be used in undertaking suitable management practices and yield prediction under changing climatic conditions in the western region of Tamil Nadu