Generalized triangular transform coding

Abstract

A general family of optimal transform coders (TC) is introduced here based on the generalized triangular decomposition (GTD) developed by Jiang, et al. This family includes the Karhunen-Loeve transform (KLT), and the prediction-based lower triangular transform (PLT) introduced by Phoong and Lin, as special cases. The coding gain of the entire family, with optimal bit allocation, is equal to those of the KLT and the PLT. Even though the PLT is not applicable for vectors which are not blocked versions of scalar wide sense stationary (WSS) processes, the GTD based family includes members which are natural extensions of the PLT, and therefore also enjoy the so-called MINLAB structure of the PLT which has the unit noise-gain property. Other special cases of the GTD-TC are the GMD (geometric mean decomposition) and the BID (bidiagonal transform). The GMD in particular has the property that the optimal bit allocation (which is required for achieving the maximum coding gain) is a uniform allocation, thereby eliminating the need for bit allocation.