Prediction of Interpolants in Subsampled Radargram Slices
Journal Title: International Journal of Trend in Scientific Research and Development - Year 2020, Vol 5, Issue 1
Abstract
This paper provides an algorithmic procedure to predict interpolants of subsampled images. Given a digital image, one can subsample it by forcing pixel values in the alternate columns and rows to zero. Thus, the size of the subsampled image is reduced to half of the size of the original image. This means 75 of the information in the original image is lost in the subsampled image. The question that arises here is whether it is possible to predict these lost pixel values, which are called interpolants so that the reconstructed image is in accordance with the original image. In this paper, two novel interpolant prediction techniques, which are reliable and computationally efficient, are discussed. They are i interpolant prediction using neighborhood pixel value averaging and ii interpolant prediction using extended morphological filtering. T. Kishan Rao | E. G. Rajan | Dr. M Shankar Lingam "Prediction of Interpolants in Subsampled Radargram Slices" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38207.pdf Paper URL : https://www.ijtsrd.com/computer-science/artificial-intelligence/38207/prediction-of-interpolants-in-subsampled-radargram-slices/t-kishan-rao
Authors and Affiliations
T. Kishan Rao | E. G. Rajan | Dr. M Shankar Lingam
Keywords
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