I've recently been updating our series on dithering to include ordered dithering. However, in order to fully demonstrate this I also updated the sample to include basic color quantizing with a fixed palette. While color reduction and dithering are related, I didn't want to cover both topics in a single blog post, therefore this post covers finding the nearest color via Euclidean distance.
Although I should really be working on adding the dithering algorithms into Gif Animator, I thought it would be useful to expand the repertoire of algorithms available for use with such tools. This article briefly mentions the expanded error diffusion algorithms that are now included, and in slightly more detail covers random dithering as well.
Another article in my C# image dithering mini-series, this time covering the Burkes error diffusion algorithm.
In my previous introductory post, I briefly described the concept of dithering an image. In this article, I will describe how to dither an image in C# using the Floyd–Steinberg algorithm.
When you reduce the number of colours in an image, it's often hard to get a 1:1 match, and so typically you can expect to see banding in an image - areas of unbroken solid colours where once multiple similar colours were present. Such banding can often ruin the look of the image, however by using dithering algorithms you can reduce such banding and greatly improve the appearance of the reduced image. This article briefly discusses dithering as a prelude to further articles with actual dithering implementations.
This post is a review (or possibly some long winded rambling) of the book [Essential Algorithms: A Practical Approach to Computer Algorithms](http://www.wiley.com/go/essentialalgorithms) by Rod Stephens and published by Wiley.