Fast Source-based Dithering for Networked Digital Video

Source-based dithering is a set of techniques designed to maximize the performance of real-time networked digital video systems that encode and decode video entirely in software. Usually frame grabber hardware presents frames in a 24 bit per pixel (bpp) format. However, most hosts are only equipped with single or eight bit deep displays and thus the color depth of the video must be reduced at some point. If the encoder reduces the color depth, the bandwidth required to carry the video on the network is lowered by a factor of 24 or 3 respectively, and the computational load is lightened on the receiving hosts. The color depth reduction algorithm must be efficient since the resulting frame rate, and thus the degree to which the illusion of motion is preserved, depends on how quickly a pixel can be processed. We use dithering algorithms chosen for efficiency and a contrast enhancement algorithm to improve image quality. 1.0 INTRODUCTION Most modern real-time networked digital video systems are either completely unable to keep up with real time video or require expensive special-purpose hardware in each video participant; thus, performance is very important to such systems. We discuss a series of technique, collectively called source-based dithering, designed to improve the performance of and minimize the loss of video quality in real-time networked digital video systems that encode and decode video in software. Usually frame grabber hardware presents individual images to a CPU in a relatively “deep” format such as “true color.” The true color format typically requires at least 24 bits to represent each pixel: 8 bits for each of the red, green, and blue components. True color display hardware is expensive, so most hosts are only equipped to display images in an eight bit deep color format or a single bit deep monochrome format. The depth of a 24 bpp image must be reduced to either 8 bpp or 1 bpp for it to be displayed on such machines. The pixel depth could in theory be reduced at either the source or destination hosts. Depth reduction at the source carries the advantages that the bandwidth required to carry the video on the network is reduced and the processing burden is reduced on receiving hosts. The source host is somewhat compensated for the work of dithering by a reduction in volume of network output processing. Depending on whether the video is reduced to 8 bpp or to 1 bpp, this technique reduces bandwidth by a factor of either 3 or 24 respectively. It is important that the color depth reduction algorithm be efficient because the resulting frame rate, and thus the degree to which the illusion of motion is preserved, depends on how quickly a pixel can be processed. Thus, we use dithering algorithms chosen for efficiency. Dithering is a technique for reducing color depth by placing a small combination of pixels with different colors within a small neighborhood so that, from a distance, the combination looks like the original color. We use a contrast enhancement algorithm to enhance the resultant picture.