Transform coder identification based on quantization footprints and lattice theory

نویسندگان

  • Marco Tagliasacchi
  • Marco Visentini Scarzanella
  • Pier Luigi Dragotti
  • Stefano Tubaro
چکیده

Transform coding is routinely used for lossy compression of discrete sources with memory. The input signal is divided into N -dimensional vectors, which are transformed by means of a linear mapping. Then, transform coefficients are quantized and entropy coded. In this paper we consider the problem of identifying the transform matrix as well as the quantization step sizes. We study the challenging case in which the only available information is a set of P transform decoded vectors. We formulate the problem in terms of finding the lattice with the largest determinant that contains all observed vectors. We propose an algorithm that is able to find the optimal solution and we formally study its convergence properties. Our analysis shows that it is possible to identify successfully both the transform and the quantization step sizes when P ≥ N + δ where δ is a small integer, and the probability of failure decreases exponentially to zero as P −N increases.

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عنوان ژورنال:
  • CoRR

دوره abs/1211.3869  شماره 

صفحات  -

تاریخ انتشار 2012