Entropy And Vision
<|reference_start|>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.<|reference_end|>
@article{kanhouche2006entropy,
    title={Entropy And Vision},
    author={Rami Kanhouche (CMLA)},
    journal={arXiv preprint arXiv:math/0606643},
    year={2006},
    archivePrefix={arXiv},
    eprint={math/0606643},
    primaryClass={math.PR cs.CV cs.DB cs.DM cs.LG math.CO}
}