Two-dimensional split and merge algorithm for differential vector quantization of images

In this paper, an image is modelled as a two and a half-dimensional surface and an approximated surface for the image is formed by triangular patches. A new two-dimensional split and merge algorithm (2DSM) for generating the approximated surface has been devised. The algorithm iteratively improves the approximated surface by splitting and merging the triangles in order to drive the error under a specified bound. In addition, a new optimal triangulation method for image data approximation is proposed. The algorithm is successfully applied for coding of monochrome images using differential vector quantization (DVQ) technique. Simulation results show that the proposed method can achieve 2.8dB improvement on the approximated image and 0.68dB improvement on the decoded image at a bit-rate lower than the current schemes. Besides, excellent reconstruction visual quality is observed. (C) 1998 Elsevier Science B.V. All rights reserved.