Adaptive Effective Wiener Filter- and Regression-Based Upsampling for Asymmetric Resolution Stereoscopic Video Coding

In asymmetric resolution stereoscopic video coding (ARSVC), a stereoscopic video consists of one full-sized left-view video sequence and the synchronized quarter-sized right-view 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 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 scheme with residual compensation 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 RTCWF-LRIPRC, 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.