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Proceedings Paper

Color image compression using neural network prediction of color components
Author(s): Syed A. Rizvi; Nader Mohsenian; Nasser M. Nasrabadi
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Paper Abstract

In this paper we present a new scheme for color image compression. The proposed scheme exploits the correlation between the basic color components (red, green, and blue: RGB) by predicting two color components given one color component. Specifically, this scheme employs neural network predictors to predict the red and blue color components using the encoded (reconstructed) green color component. The prediction error is further quantized using vector quantization. The performance of the proposed scheme is evaluated and compared with that of the JPEG.

Paper Details

Date Published: 4 March 1996
PDF: 10 pages
Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); doi: 10.1117/12.234260
Show Author Affiliations
Syed A. Rizvi, SUNY/Buffalo (United States)
Nader Mohsenian, IBM Microelectronics (United States)
Nasser M. Nasrabadi, SUNY/Buffalo (United States)

Published in SPIE Proceedings Vol. 2664:
Applications of Artificial Neural Networks in Image Processing
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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