Liping Wang

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In modern video coding standards, for example H.264, fractional-pixel motion estimation (ME) is implemented. Many fast integer-pixel ME algorithms have been developed to reduce the computational complexity of integer-pixel ME. With these advancements, fractional-pixel ME becomes the new bottleneck in the implementation of video encoders. For example, the(More)
In this paper, a novel weighted cross prediction (WCP) mode is proposed to replace DC mode in Intra_4x4 prediction of H.264/AVC. In the proposed scheme, the upper right part of one 4x4 block mainly employs vertical prediction while the lower left part mainly uses horizontal prediction, predicting both in vertical and horizontal directions in one block. This(More)
Adaptive Intra Mode Bit Skip (AIMBS) technique using boundary pixels smoothness has been shown to achieve coding efficiency improvement for H.264/AVC's Intra_4x4 coding in relatively large QPs. However, the DC mode in the Multiple-Prediction of the AIMBS becomes much less effective. To tackle this problem and further improve the coding efficiency,(More)
In this paper, a new compensated sum of absolute difference (CSAD) for fast H.264 inter mode selection algorithm is proposed. The main idea is to determine the best inter mode based on CSAD cost instead of the rate-distortion (RD) cost. This approach can avoid most of the computationally intensive processes in the H.264 mode decision. The CSAD could solve(More)
In this paper, an enhanced sum of absolute integer transform difference (ESAITD) cost function with rate predictor “sum of non-zero coefficient frequencies” from CAVLC-based rate estimation is proposed for Intra_4x4 mode decision in H.264/AVC. This rate predictor is using simple but significant parameter to approximate the total encoded bitrate accurately.(More)
Adaptive intra mode bit skip (AIMBS) can improve the coding efficiency of intra coding in H.264/AVC. However, it has two shortcomings: one is that DC mode is not effectively handled in AIMBS as DC mode is duplicated in both Single-Prediction and Multiple-Prediction processing; the other is that AIMBS does not well match the most probable mode (MPM)(More)
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