Entropy And Vision
概率论
2007-05-23 v3 计算机视觉与模式识别
数据库
离散数学
机器学习
组合数学
摘要
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.
引用
@article{arxiv.math/0606643,
title = {Entropy And Vision},
author = {Rami Kanhouche},
journal= {arXiv preprint arXiv:math/0606643},
year = {2007}
}