Dr. Necaise presented a very interesting and enlightening presentation on color image quantization. He began by informing us of the various areas using quantization, which include: math, communications, voice recognition, finger print matching, computer vision, image processing, and computer graphics. He defined color quantization, as the process of reducing the number of colors needed for the display or storage of an image while maintaining the appearance of the original. A prime example of the need for color image quantization can be described via monitors and printers. Most of these devices are limited to working with an undetermined palette of 256 colors. Many images that need to be displayed are composed of far more colors than these devices can handle. Therefore, it is imperative to have a method for reducing the number of colors contained in an image in order to display that image on a device with limited color capabilities. Another popular example is the handling of color images by web browsers.

Areas of quantization in computer graphics have evolved from previous work done in the areas of digital image processing and communications. Due to the popularity of "High-Definition" television, research in this area is also very popular. Other useful areas for computer graphics include data compression, edge detection and volume rendering.

Following the introduction, Dr. Necaise presented a formal definition and described the process of color image quantization, which include:

1. Sampling the original image for color statistics.
2. Choosing a color map based on those statistics.
3. Mapping the colors to their representative in the color map.
4. Quantizing and drawing the new image.

There are two major algorithm groups for quantizing images: Iterative (concentrates on quality) and heuristic (concentrates on speed). Dr. Necaise presented a detailed description of the K-Means iterative algorithm and of 3-3-3 adaptive heuristic algorithm.

He concluded his presentation with his discussion on three popular algorithms:

• Median Cut Algorithm
• Center Cut Algorithm
• Color Cut Algorithm

The Color Cut Algorithm utilizes a combination of the best techniques from other algorithms and was developed by Dr. Necaise.