Abstract
In this paper, a new 2D split and merge algorithm (2DSM) for image coding is devised. An image is modelled as a 2.5-dimensional surface and approximated by a surface formed by triangular patches. The algorithm iteratively improves the approximated image by splitting the merging of the triangles in order to drive the error under a specified bound. In addition, a new optimal triangulation for image data approximation is proposed. The algorithm is successfully applied for coding monochrome images using Interpolative Vector Quantization (IVQ) technique. Simulation results show that the proposed method can achieve 2.8 dB improvement on the approximated image and 0.68 dB improvement on the decoded image at a bit rate lower than the current schemes. Besides, excellent reconstruction visual quality is observed.
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