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“Advanced Techniques for High Fidelity Video Coding”
by Qi Zhang
August 2010
This research focuses on two advanced techniques for high-bit-rate video coding: 1) subpel motion estimation and 2) residual processing.
First, we study sup-pixel motion estimation for video coding. We analyze the characteristics of the sub-pel motion estimation error surface and propose an optimal subpel motion vector resolution estimation scheme that allows each block with different characteristics to maximize its RD gain through a flexible motion vector resolution. Furthermore, a direct subpel MV prediction scheme is proposed to estimate the optimal subpel position. The rate-distortion performance of the proposed motion prediction scheme is close to that of full search while it demands only about of 10% of the computational complexity of the full search.Secondly, we investigate high-bit-rate video coding techniques for high definition video contents. We observed that under the requirements of high-bit-rate coding, there still left a large portion of uncompensated information in the prediction residual that represents similar signal characteristics of _lm grain noise. Due to small quantization step size used by high-bit-rate coding, these untreated small features render all existing coding schemes ineffective. To address this issue, a novel granular noise prediction and coding scheme is proposed to provide a separate treatment for these residuals. A frequency domain- based prediction and coding scheme is proposed to enhance the coding performance. The proposed granular noise prediction and coding scheme outperforms H.264/AVC by an average of 10% bit rate saving.
Thirdly, we further investigate on the impact of high-bit-rate coding from the more fundamental signal characteristics point of view. A probability distribution analysis on DCT coefficients from the H.264/AVC codec under different bit rates is conducted to reveal that the prediction residual in the form of DCT coefficients have a near uniform distribution for all scanning positions. To further understand this phenomenon, a correlation based analysis was conducted to show that the different types of correlations existed in the video frame and the distribution of these correlations highly impact the coding efficiency. A significant amount of short and medium-range correlations due to the use of a fine quantization parameter cannot be easily removed by existing compensation techniques. Consequently, the video coding performance degrades rapidly as quality increases. A novel Multi-Order-Residual (MOR) coding scheme was proposed. The concept is based on the numerical analysis to extract different correlation through different phases. A different DCT-based compensation and coding scheme combined with an improved rate-distortion optimization process was proposed to target the higher-order signal characteristics. An additional pre-search coefficient optimization phase was proposed to further enhance compression performance. Experimental results show that the proposed MOR scheme outperforms H.264/AVC by an average of 16% bit rate savings.