In asymmetric resolution stereoscopic video coding (ARSVC), a stereoscopic video consists of one full-sized leftview video sequence and the synchronized quarter-sized rightview video sequence for achieving a bitrate reduction effect by the encoder. Prior to displaying 3D scenes on the screen, it is necessary to upsample the decoded downsampled right-view video sequence at the client side. In this paper, we propose an effective adaptive upsampling method for ARSVC. First, we employ the resolution- and texture-consistency (RTC) consideration in the conventional Wiener filter-based interpolation scheme, called RTCWF, to enhance the upsampling accuracy in the spatial domain. Second, we propose a linear regression-based interview prediction (LRIP) scheme with residual compensation (RC), called LRIPRC, to increase the upsampling accuracy in the interview domain. Third, we propose an adaptive fusion-based approach to integrate RTCWF and LRIPRC, called RTCWFLRIPRC, to maximize the quality improvement of the upsampled image. Based on seven typical test stereoscopic video sequences, in 3D-HEVC, the experimental results demonstrated that in terms of six well-known quality metrics and execution time requirements, our RTCWF-LRIPRC method outperforms the state-of-the-art upsampling methods for ARSVC.

In the piecewise function evaluation with polynomial approximation, nonuniform segmentation can effectively reduce the size of lookup tables for some arithmetic functions compared to uniform segmentation approaches, at the cost of the extra segment address (index) encoder that results in area and delay overhead. Also, it is observed that the nonuniform segmentation reflects a design tradeoff between the ROM size and the area cost of the subsequent arithmetic computation hardware. In this paper, we propose a new nonuniform segmentation method that searches for the optimal segmentation scheme with the goal of minimized ROM, total area, or delay. For some high-variation arithmetic functions, the proposed segmentation method achieves significant area reduction compared to the uniform segmentation method. We also demonstrate the design tradeoff among uniform and nonuniform segmentation, and degree-one and degree-two polynomial approximations, with respect to precision ranging from 12 to 32 bits for the elementary function of reciprocal.