This paper describes a technique to compress images based on vector quantization. The vector quantizer is designed to reduce both perceptual irrelevancy and mathematical redundancy. This is done without using transforms and entropic coding, which are normally used respectively prior and after quantization. Because of its structure, the vector quantizer can be implemented efficiently as a unifor...

This paper is the extension of two-stage vector quantization–(spherical) lattice vector quantization (VQ–(S)LVQ) recently introduced by Pan and Fischer [1]. First, according to high resolution quantization theory, generalized vector quantization–lattice vector quantization (G-VQ–LVQ) is formulated in order to release the constraint of the spherical boundary for the second-stage lattice vector q...

We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a recently developed topographical feature hierarchy to provide a view-based representation of threedimensional objects using a dynamical vector quantization approach. For a simple short-term object memory model we demonstr...

common spatial pattern (csp) is a method commonly used to enhance the effects of event‑related desynchronization and event‑related synchronization present in multichannel electroencephalogram‑based brain‑computer interface (bci) systems. in the present study, a novel csp sub‑band feature selection has been proposed based on the discriminative information of the features. besides, a distinction ...

We consider images of boar spermatozoa obtained with an optical phase-contrast microscope. Our goal is to automatically classify single sperm cells as acrosome-intact (class 1) or acrosome-reacted (class 2). Such classification is important for the estimation of the fertilization potential of a sperm sample for artificial insemination. We segment the sperm heads and compute a feature vector for...

This paper presents a multiresolution adaptive vector quantization and perceptual based multiview image coding scheme. It decorrelates the input views into a number of subbands using a lifting based wavelet transform. The coefficients in the same subbands of different views are divided into vectors and then joined together. The resulting vectors are then vector quantized using an adaptive vecto...

Very fast tree-structured vector quantization employs scalar quantization decisions at each level, but chooses the dimension on which to quantize based on the coordinate direction of maximum variance. Because the quantization is scalar, searches are no more complex than scalar quantization − providing significant improvement in complexity over full-searched or even tree-structured vector quanti...