Abhijit Sarkar

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The variability among color-normal observers poses a challenge to modern display colorimetry because of their peaky primaries. But such devices also hold the key to a future solution to this issue. In this paper, we present a method for deriving seven distinct colorimetric observer categories, and also a method for classifying individual observers as(More)
In this paper, a thin ice thickness algorithm for coastal polynyas in the Chukchi and Beaufort Seas has been attempted which uses the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) 89-GHz brightness temperature data at a 6.25-km resolution. Thermal ice thickness estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS)(More)
Invité Mme. Sabine Süsstrunk Professeur, School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Suisse M. Mark Fairchild Professeur, Centre for Imaging Science, Rochester Institute of Technology, Etats-Unis Mme. Françoise Viénot Professeur MNHN (Muséum National d’Histoire Naturelle), Centre de Recherche sur la(More)
A parallel algorithm is developed for the domain decomposition of uncertain dynamical systems defined by stochastic partial differential equations. The methodology is particularly amenable to parallel processing for effective exploitation of the computational and storage capability of currently available multiprocessing computational environment. The(More)
Various recent studies have shown that observer variability can be a significant issue in modern display colorimetry, since narrow-band primaries are often used to achieve wider color gamuts. As far as industrial applications are concerned, past works on various aspects of observer variability and metamerism have mostly focused on cross-media color(More)
This paper compares CIE 2006 model predictions and the 1964 10° standard colorimetric observer with the average observer data from three distinct subgroups of 47 Stiles-Burch observers formed on the basis of observer ages. For two of these subgroups, the long-wave sensitive (x-) color matching functions obtained from the CIE 2006 model did not accurately(More)
It is known that wave period can be estimated from altimeter measurements of wave height, wind speed, radar backscatter cross section, etc., using empirical relationship. Of late, the data adaptive approach of neural networks has been used to derive wave period from altimeter data, and it has been shown that the technique appears to be superior compared to(More)