Finite State Vector Quantization With Virtual Super Codebook Extended by Affine Transform

摘要

In this paper, the finite-state vector quantizers (FSVQs) with an extended super codebook obtained by applying the affine transformation to the codewords are proposed for the image coding framework. In designing the state codebook, each codeword in the super codebook in conventional FSVQs is affine-transformed (luminance shift, contrast scaling, and isometry operations) and thus a much larger virtual codebook is obtained. By using the matching criteria, such as the gradient match and the side match criteria in existing FSVQs, for the neighboring pixels in the block boundaries the much smaller state codebooks with different sizes can be constructed. Note that the rest parts of the proposed scheme are similar to those in the conventional FSVQs. On the other hand, much higher image quality can be obtained by using the extended virtual codebook. According to our simulation results, the peak-signal-to-noise ratio (PSNR) of the decoded images is significantly improved by 1-2 dB for the extended virtual codebook. However, the PSNRs are significantly reduced once the FSVQ with the gradient match and side match criteria are employed. Therefore we proposed another scheme that can improve the PSNR under the same bit rate. The simulation results show that the PSNR can be slightly increased. According to this scheme, we will propose efficient scheme to significantly increase the PSNR in our future work.