Low-complexity interpolation coding for server-based computing

Abstract

Summary form only given. The growing total cost of ownership has resulted in a shift away from the distributed model of desktop computing toward a more centralized server-based computing (SBC) model. In SBC, all application logic is executed on the server while clients simply process the resulting screen updates sent from the server. To provide good performance, SBC systems employ various techniques to encode the screen updates to minimize the bandwidth and processing requirements of sending the screen updates. However, existing SBC encoding techniques are not able to effectively support multimedia applications. To address this problem, we have developed a family of linear interpolation algorithms for encoding SBC screen updates. We first present an overview of an optimal linear interpolation (OLI) algorithm. Given a rectangular region of pixels to be encoded, OLI represents the region as a one-dimensional function, mapping from the cardinal number of each pixel to the color value of the pixel. To reduce encoding complexity, we developed two linear interpolation algorithms with linear encoding and decoding computational complexity. The algorithms are near optimal linear interpolation (NOLI) and 2-D lossless linear interpolation (2DLI). We have implemented our linear interpolation algorithms and compared their performance with other approaches on discrete-toned and smoothed-toned images.