Abstract
In this paper, a novel content adaptive rate-distortion optimization scheme has been proposed. The scheme could effectively distinguish texture region, edge region and flat region using directional field technique. Since the Human Vision System (HVS) perceives distortions more easily near edges and in flat regions, distortion reduction is more important in those regions than the bits it consumes to code the motion information. The adaptive rate-distortion optimization is carried out by adjusting the Lagrangian multiplier so that small values are assigned to edge and flat regions and large values to the random texture region. The proposed scheme has been tested in the scalable video coding (SVC) reference codec by Microsoft Research Asia (MSRA) [1]. Experimental results have shown that the accuracy of motion alignment in the visually important region is greatly improved in the temporal transform step of 3D wavelet coding and the scheme effectively preserves details in the most perceptually prominent regions for all bitstream layers with no loss in PSNR.