• DocumentCode
    298446
  • Title

    Mixture density estimation under the existence of mixels

  • Author

    Kitamoto, Asanobu ; Takagi, Mikio

  • Author_Institution
    Inst. of Ind. Sci., Tokyo Univ., Japan
  • Volume
    1
  • fYear
    34881
  • fDate
    10-14 Jul1995
  • Firstpage
    121
  • Abstract
    The paper focuses on a mixed pixel or mixel. In the mixture density estimation problem, the authors include implicit distributions produced by mixels, in addition to the explicit distributions produced by pure pixels. NOAA-AVHRR channel 5 images are classified into several categories including mixel categories based on a Bayesian decision rule, and three optimization schemes are compared
  • Keywords
    Bayes methods; decision theory; geophysical signal processing; image classification; maximum likelihood estimation; optimisation; remote sensing; statistical analysis; Bayesian decision rule; NOAA-AVHRR channel 5 images; explicit distributions; implicit distributions; mixed pixel; mixels; mixture density estimation; optimization schemes; Argon; Bayesian methods; Biomedical imaging; Density functional theory; Gaussian distribution; Probability density function; Random variables; Remote sensing; Shape; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
  • Conference_Location
    Firenze
  • Print_ISBN
    0-7803-2567-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.1995.519666
  • Filename
    519666