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
Link To Document