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July 1, 1982ACM SIGGRAPH Computer Graphics548 citations

Color image quantization for frame buffer display

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PHPaul S. HeckbertCarnegie Mellon University

Key Points

  • To develop adaptive, tapered color quantization algorithms capable of rendering high-quality color images on memory-limited frame buffer hardware.
  • Decomposed the color quantization pipeline into four distinct phases: color distribution sampling, colormap selection, nearest-neighbor color mapping, and redrawing with optional dithering.
  • Designed and evaluated multiple adaptive quantization algorithms across these phases against traditional uniform quantization methods.
  • Demonstrated that color images typically requiring 15 bits per pixel can be compressed to 8 or fewer bits per pixel with minimal subjective quality loss.
  • Produced reconstructed images with noticeably superior visual fidelity compared to results from uniform quantization.

Abstract

Algorithms for adaptive, tapered quantization of color images are described. The research is motivated by the desire to display high-quality reproductions of color images with small frame buffers. It is demonstrated that many color images which would normally require a frame buffer having 15 bits per pixel can be quantized to 8 or fewer bits per pixel with little subjective degradation. In most cases, the resulting images look significantly better than those made with uniform quantization. The color image quantization task is broken into four phases: 1) Sampling the original image for color statistics 2) Choosing a colormap based on the color statistics 3) Mapping original colors to their nearest neighbors in the colormap 4) Quantizing and redrawing the original image (with optional dither). Several algorithms for each of phases 2-4 are described, and images created by each given.

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Cite This Study

Paul S. Heckbert (1982) studied this question.

synapsesocial.com/papers/69ffcfe1581c6e761e778ff0https://doi.org/10.1145/965145.801294
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