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ICMCS
2006
IEEE

Image Vector Quantization Indices Recovery using Lagrange Interpolation

14 years 5 months ago
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 orde...
Yung-Gi Wu, Chia-Hao Wu
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICMCS
Authors Yung-Gi Wu, Chia-Hao Wu
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