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Proceedings Paper

Color palette restoration
Author(s): Barbara E. Schmitz; Robert L. Stevenson
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Paper Abstract

When designing hardware, it is often desirable to represent images as economically as possible. Due to this, algorithms have been developed to create reduced palette images. Much better viewing results can be obtained by first reconstructing a full color image from the reduced palette image. This creates a need for a palette restoration algorithm. This paper develops an algorithm to reconstruct high resolution color image data from reduced color palette images. The algorithm is based on stochastic regularization using a non-Gaussian Markov random field model for the image data. This results in a constrained optimization algorithm that is solved using an iterative constrained gradient descent computational algorithm. During each iteration the potential update must be projected onto the constraint space. In this paper a projection operator that maps a vector onto a quantized constraint space is developed. Results of the proposed palette restoration algorithm have indicated that it is effective for the reconstruction of palettized images. Quantitative as well as visual results of the experiments are presented.

Paper Details

Date Published: 1 May 1994
PDF: 12 pages
Proc. SPIE 2179, Human Vision, Visual Processing, and Digital Display V, (1 May 1994); doi: 10.1117/12.172684
Show Author Affiliations
Barbara E. Schmitz, Univ. of Notre Dame (United States)
Robert L. Stevenson, Univ. of Notre Dame (United States)


Published in SPIE Proceedings Vol. 2179:
Human Vision, Visual Processing, and Digital Display V
Bernice E. Rogowitz; Jan P. Allebach, Editor(s)

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