Entropy And Vision

In vector quantization the number of vectors used to construct the codebook is always an undefined problem, there is always a compromise between the number of vectors and the quantity of information lost during the compression. In this text we present a minimum of Entropy principle that gives solution to this compromise and represents an Entropy point of view of signal compression in general. Also we present a new adaptive Object Quantization technique that is the same for the compression and the perception.

Data and Resources

Additional Info

Field Value
Source https://hal.science/hal-00081913
Author Kanhouche, Rami
Maintainer CCSD
Last Updated May 9, 2026, 20:55 (UTC)
Created May 9, 2026, 20:55 (UTC)
Identifier hal-00081913
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Centre de Mathématiques et de Leurs Applications (CMLA) ; École normale supérieure - Cachan (ENS Cachan)-Centre National de la Recherche Scientifique (CNRS)
creator Kanhouche, Rami
date 2006-07-15T00:00:00
harvest_object_id c7fff62b-d797-44c0-ac92-ff86a61d166b
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2024-04-09T00:00:00
relation info:eu-repo/semantics/altIdentifier/arxiv/math.PR/0606643
set_spec type:UNDEFINED