Paper
1 May 1994 Color palette restoration
Barbara E. Schmitz, Robert L. Stevenson
Author Affiliations +
Proceedings Volume 2179, Human Vision, Visual Processing, and Digital Display V; (1994) https://doi.org/10.1117/12.172684
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States
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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Barbara E. Schmitz and Robert L. Stevenson "Color palette restoration", Proc. SPIE 2179, Human Vision, Visual Processing, and Digital Display V, (1 May 1994); https://doi.org/10.1117/12.172684
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Quantization

Reconstruction algorithms

Algorithm development

Image processing

Image analysis

Image resolution

Space operations

Back to Top