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Estimation of the Embedding Capacity in Pixel-pair based Watermarking Schemes
Abstract
Embedding capacity estimation is an interesting and
important problem specifically in reversible multi-pass water
marking and is required for analysis before any image can be
watermarked. In this paper, we propose an efficient method for
estimating the embedding capacity of a given cover image under
multi-pass embedding, without actually embedding the watermark. We
demonstrate this for a class of reversible wa-
termarking schemes which operate on a disjoint group of pixels,
specifically for pixel pairs. We propose an algorithm to iteratively
update the co-occurrence matrix at every stage to estimate the
multi-pass embedding capacity. Further we show how we can exploit the
sparsity of the co-occurrence matrix to make these algorithms extremely
efficient. Hence these algorithms, though iterative are computationally
much more efficient vis-a-vis actual watermarking. We also suggest an
extremely efficient, pre-computable tree based implementation which is
conceptuallysimilar to the co-occurrence based method, but provides the
estimates in a single iteration, requiring a complexity akin to that of
single pass capacity estimation. We also provide bounds
on the embedding capacity. We finally show how our method
can be easily used on a number of watermarking algorithms and
specifically evaluate the performance of our algorithms on the
benchmark watermarking schemes of Tian and Coltuc et
al.
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