An orientation normalized vector quantizer for flow-like image coding

A new vector quantization image coding scheme called orientation normalized vector quantizer (ONVQ) is presented. During the encoding process, the orientation field of an image is first calculated and recorded using a quad-tree data structure; then, the image is partitioned into digitalized round blocks. These round blocks are normalized to the horizontal direction according to their original orientation and the vector which is quantized. The decoder obtains reproduction vectors from a codebook, and restores them to their original orientations. Since blocks of different orientations can use the same codeword, ONVQ needs a much smaller codebook; therefore, low bit rates are achieved (0.6-0.8 bpp for 256×256 images). The subjective quality of ONVQ-coded images is more satisfying than that obtained by a simple vector quantization scheme