A Technique for Producing Scalable Color-Quantized Images With Error Diffusion

Abstract

Abstract-To reliably and efficiently deliver media information to diverse clients over heterogeneous networks, the media involved must be scalable. In this paper, a color quantization algorithm for generating scalable colorindexed images is proposed based on a multiscale error diffusion framework. Images of lower resolutions are embedded in the outputs such that a simple down-sampling process can extract images of any desirable resolutions. Images possessing this scalable property support transmission over the Internet which contains clients with different display resolutions, systems with different caching resources and networks with varying bandwidths and QoS capabilities. Unlike most of the color halftoning algorithms available nowadays, the proposed algorithm is not dedicated for printing applications but for color-indexed displays. It works with any arbitrary palettes of different size.Index Terms-Color index, color quantization, directional hysteresis, error diffusion, halftoning, multiscale processing, scalable media.

A Common Palette Creation Algorithm for Multiple Images with Transparency Information

“…This method combines the K-Means clustering algorithm to create the color palette. A technique for producing scalable color quantized images is introduced in [6]. Other color image quantizing methods such as agglomerative clustering [7], sequential scalar quantization [8], kohonen neural networks [9], model based method [10], dynamic programming [11] are available in literature.…”