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Proceedings Paper

Scattered data interpolation algorithm for still-image subsampling and for motion-field representations used for video coding
Author(s): Herve Le Floch; Claude Labit
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Paper Abstract

In this paper, the Shepard interpolation algorithm has ben used for a compact still image representation and for motion estimation in video sequences. In the context of still image representation, the goal is to compute the values and the locations of a fixed number of samples to approximate efficiently a natural grey-level image. These values will be found by a relaxation process. In the context of image coding, samples values and samples locations have to be coded. A quantization is applied on the samples values and thus reduces the amount of information. Samples locations are represented through a binary image which is coded using an arithmetic coder. In the context of motion estimation scheme, the Shepard interpolation algorithm has been used to construct a dense vector field from few vectors. This dense vector field is used to predict the current frame. Three schemes are presented. In the first scheme, vectors are regularly located and a relaxation algorithm is used to compute the 'best' vector values. In the two following schemes, a relaxation method is used to compute the 'best' locations and the 'best' values of the vectors. Experimental results are provided using several images and video sequences showing the efficiency of such non-uniform sampling process of data.

Paper Details

Date Published: 10 January 1997
PDF: 12 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263275
Show Author Affiliations
Herve Le Floch, IRISA/INRIA-Rennes (France)
Claude Labit, IRISA/INRIA-Rennes (France)

Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp III, Editor(s)

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