Reconstruction of lost blocks using codeword estimation
IEEE Transactions on Consumer Electronics
Robust vector quantization for wireless channels
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Image Processing
A new image coding algorithm using variable-rate side-match finite-state vector quantization
IEEE Transactions on Image Processing
Error-resilient pyramid vector quantization for image compression
IEEE Transactions on Image Processing
Noise reduction of VQ encoded images through anti-gray coding
IEEE Transactions on Image Processing
Information loss recovery for block-based image coding techniques-a fuzzy logic approach
IEEE Transactions on Image Processing
Boundary matching detection for recovering erroneously received VQ indexes over noisy channels
IEEE Transactions on Circuits and Systems for Video Technology
Image vector quantization codec indices recovery using Lagrange interpolation
Image and Vision Computing
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In the past few years, many techniques have been explored to investigate the transmission of VQ indices over noisy channels. In this paper, we propose an algotithm to correct or conceal the channel errors found in a VQ encoded image. In the proposed method, some verification information (i.e., the checksums) is embedded into the MSB of the indices of the VQ encoded data. This information can help with the detection of errors in the indices transmitted over a noisy channel. Before embedding, the codebook is rearranged and the binary indices are assigned to the codewords in such a way that the MSB-differing vectors are as close as possible to each other. In addition, a new error concealment technique is proposed to correct the erroneous image. According to our experiments, the proposed scheme provides a detection result with greater than a 96% probability of detection in the BER 0.01 noisy channel. Compared to the related method, Anti-Gray Coding (AGC), the proposed method performs better under BER 10-3-10-2. Moreover, our method does not have the phenomenon of false alarm that occurs in AGC. Therefore, our method is very suitable to more noisy channels-including mobile ones.