Image Vector Quantization Indices Recovery using Lagrange Interpolation

Vector quantization (VQ) is an efficient coding algorithm due to its fast decoding efficiency. Indices of VQ will be lost during the transmission because of the signal interference. In this paper, we propose an efficient estimation method by using the Lagrange interpolation formula to recover the lost indices in image vector quantization codec. If the image or video has the limitation of the period of validity, re-transmitting the data wastes of time. Therefore, using the received correct data to estimate and recover the lost data is efficient in time-constraint situation such as network conference. For nature image or video, the pixels with its neighbors are correlative. Since the VQ partitions the image into sub-blocks and quantize them to form the indices to transmit, the correlation between adjacent indices is very strong. There are two important parts of the proposed method. One is preprocessing process and the other is the estimation process. In preprocessing, we modify the order of code-vectors in the VQ codebook to increases the correlation between neighboring vectors. On the second part, the recovery process on the decoder, using the Lagrange interpolation formula to constitute a polynomial to describe the tendency of VQ indices, and use the polynomial to estimate the lost VQ indices. The simulation results demonstrate that our method can efficient estimate the lost indices in acceptable visual quality