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In recent times, customers have shifted their focus to offshoring vendors' ability to provide high quality software, in addition to the cost advantages. The present research highlights how knowledge management (KM) impacts through different factors on software quality in offshore development projects executed by vendors. A survey of 70 project managers engaged in offshoring at a mid size Indian Software Company was carried out and the collected data were analyzed using SPSS package.

Per pixel classification algorithms are incapable of mapping the land cover classes at its sub pixel level. The solution to this problem is to make the spatial resolution finer than the original data and arrange the sub pixels according to the fractional cover of each of the classes in the pixel and their class distribution in neighboring pixels. In this paper, an algorithm, named as 'pixel filling algorithm' for super resolution mapping has been proposed. The algorithm considers the information from the neighboring pixels of pixel to be super-resolved and treats all the classes equal to produce fine spatial resolution maps. The performance of the algorithm has been tested on a synthetic dataset as well as on a hyperspectral data. The datasets were reduced by Daubechies 4 wavelets and then a 3x3 filter was applied to make the datasets coarser. The overall accuracy of super resolution algorithm for synthetic data and hyperspectral data are calculated as 96.3 percent and 83.6 percent, respectively for the whole data and 86.3 percent and 70.8 percent, respectively for super resolved mixed pixels.Index Terms-super resolution; hyperspectral data; sub pixel mapping; Pixel Filling.

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