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In this work, results of psychovisual studies of the human visual system are discussed and interpreted in a mathematical framework. the formation of the perception is described by appropriate minimization problems and the ...

New schemes for classification of images are suggested. An application of these methods in adaptive DCT of images is considered. A new method to combine classification and bit allocation is introduces. Also, an efficient ...

We consider the problem of detecting a discrete Markov source which is transmitted across a discrete memoryless channel. The detection is based upon the maximum a posteriori (MAP) criterion which yields the minimum probability ...

Under noiseless channel conditions and for sources with memory, finite-state vector quantizers (FSVQs) exhibit improvements over memoryless vector quantizers. It is shown, however, that in the presence of channel noise, ...

The performance of the reflection symmetric residual quantizer (rRQ) on various types of sources is tested and certain conclusions about its capabilities and limitations are drawn. rRQ is then used to design several ...

The finite-state vector quantizer (FSVQ), introduced by Foster, Dunham and Gray, is a finite-state machine that can be viewed as a collection of memoryless full-searched vector quantizers, where each input vector is encoded ...

In this paper, results of phychovisual studies of the human visual system are discussed and interpreted in a mathematical framework. The formation of the perception is described by appropriate minimization problems and the ...

The fixed-rate structured vector quantizer (SVQ) derived from a variable-length scalar quantizer was originally proposed for quantizing stationary memoryless sources. In this paper, the SVQ has been extended to a specific ...

We evaluate the performance of several multiterminal detection systems, each of which comprises a central detector and a network of remote sensors. The function of the sensors is to collect data on a random signal source ...

This paper describes a structured vector quantization approach for stationary memoryless sources that combines the scalar-vector quantizer (SVQ) ideas (Laroia and Farvardin) with trellis coded quantization (Marcellin and ...