Inverse error diffusion using table look-up and vector quantization: a novel scheme for low bit rate

This paper considers inverse error diffusion and data compression of binary error diffused images using table look-up and vector quantization (VQ). The encoding process needs a table look-up which transforms half-toned images to a set of codewords. The decoding process requires table look-up and low pass filtering. Using the proposed scheme the reconstructed gray-scale image is stored in a compressed form, Also, the error diffused image can be compressed in the gray-scale domain. Our method integrates the processes of inverse halftoning and compression and is useful when error diffusion halftoning algorithm is applied. The proposed scheme outperforms, for low bit rate (0.25 bpp to 0.5 bpp), similar existing techniques and is of low computational complexity.