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This article proposes a fast mode decision algorithm based on the correlation of the just-noticeable-difference (JND) and the rate distortion cost (RD cost) to reduce the computational complexity of H.264/AVC. First, the relationship between the average RD cost and the number of JND pixels is established by Gaussian distributions. Thus, the RD cost of the Inter 16 × 16 mode is compared with the predicted thresholds from these models for fast mode selection. In addition, we use the image content, the residual data, and JND visual model for horizontal/vertical detection, and then utilize the result to predict the partition in a macroblock. From the experimental results, a greater time saving can be achieved while the proposed algorithm also maintains performance and quality effectively.

Fast mode decision based on human noticeable luminance difference and rate distortion cost for H.264/AVC