This paper presents two techniques to boost the quantization performance of trelli-based beamforming vector quantization schemes [?], [?]. It is well known that tail-biting trelli...
Vector Quantization is useful for data compression. Competitive Learning which minimizes reconstruction error is an appropriate algorithm for vector quantization of unlabelled dat...
Besides their topological properties, Kohonen maps are often used for vector quantization only. These auto-organised networks are often compared to other standard and/or adaptive v...
It is well-known that the time and memory necessary to create a codebook from large training databases have hindered the vector quantization based systems for real applications. T...
Paulo Sergio Lopes de Souza, Alceu de Souza Britto...
In this paper, an original method named GNG-T, extended from GNG-U algorithm by [1] is presented. The method performs continuously vector quantization over a distribution that chan...
Abstract. We present a fast resampling scheme using vector quantization. Our method di ers from prior work applying vector quantization to speeding up image and volume processing i...
— Many image compression techniques require the quantization of multiple vector sources with significantly different distributions. With vector quantization (VQ), these sources ...
: While lattice vector quantization (LVQ) can solve the complexity problem of LBG based vector quantizers, and also yield very general codebooks, a single stage lattice VQ, when ap...
We describe the QccPack software package, an open-source collection of library routines and utility programs for quantization, compression, and coding of data. QccPack is being wr...
Abstract. Vector quantization (VQ) is an elementary technique for image compression. However, the complexity of searching the nearest codeword in a codebook is time-consuming. In t...