• DocumentCode
    1748846
  • Title

    A self-organizing map with dynamic architecture for efficient color quantization

  • Author

    Kirk, James S. ; Chang, Dar-Jen ; Zurada, Jacek M.

  • Author_Institution
    Comput. Sci. & Eng. Program, Louisville Univ., KY, USA
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2128
  • Abstract
    Color quantization is often used to convert 24-bit RGB images to 8-bit palette-table images. However, in some cases, the imposed 8 bits per pixel may be too stringent to adequately represent the image. For other images, 8 bits per pixel are unnecessarily generous. For image storage and transmission, it is important to compress an image as much as possible without exceeding an allowable level of degradation. The paper describes the use of a dynamically-growing self-organizing map (SOM) to determine the palette-table required to adequately represent the colors of an RGB image, given an allowable degree of quantization error
  • Keywords
    data compression; image coding; image colour analysis; learning (artificial intelligence); neural net architecture; self-organising feature maps; RGB image; color quantization; dynamic architecture; image compression; image storage; image transmission; quantization error; self-organizing map; Color; Computer architecture; Computer science; Image converters; Image storage; Kirk field collapse effect; Neurons; Pixel; Prototypes; Quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.938495
  • Filename
    938495