Spectral entropy-based quantization matrices for H.264/AVC video coding

In transform-based compression schemes, the task of choosing, quantizing, and coding the coefficients that best represent a signal is of prime importance. As a step in this direction, Yang and Gibson [1] have designed a coefficient selection scheme based on Campbell's coefficient rate and spectral entropy [2]. Building on their coefficient selection mechanism, we develop a method to allocate bits amongst the chosen coefficients that can outperform the classical method under certain conditions. We then design quantization matrices (QMs) based on the proposed bit allocation scheme. Results show that the newly designed QMs perform better than the default QMs for H.264/AVC encoding in terms of both peak signal to noise ratio (PSNR) and structural similarity (SSIM). The proposed method entails delay but is not computationally intensive.