Choice of a 2-D causal autoregressive texture model using information criteria
Pattern Recognition Letters
A numerical algorithm for stable 2D autoregressive filter design
Signal Processing
Adapted generalized lifting schemes for scalable lossless image coding
Signal Processing
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This paper is mainly devoted to the derivation of a new two-dimensional fast lattice recursive least squares (2D FLRLS) algorithm. This algorithm updates the filter coefficients in growing-order form with linear computational complexity. After appropriately defining the “order” of 2D data and exploiting the relation with 1D multichannel, “order” recursion relations and shift invariance property are derived. The geometrical approaches of the vector space and the orthogonal projection then can be used for solving this 2D prediction problem. We examine the performances of this new algorithm in comparison with other fast algorithms