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 this paper, we propose a novel and effective hybrid method, which joins the conventional chroma subsampling and the distortion-minimization-based luma modification together, to improve the quality of the reconstructed RGB fullcolor image. Assume the input RGB full-color image has been transformed to a YUV image, prior to compression. For each 2×2 UV block, one 4:2:0 subsampling is applied to determine the one subsampled U and V components, Us and Vs. Based on Us, Vs, and the corresponding 2×2 original RGB block, a main theorem is provided to determine the ideally modified 2×2 luma block in constant time such that the color peak signalto-noise ratio (CPSNR) quality distortion between the original 2×2 RGB block and the reconstructed 2×2 RGB block can be minimized in a globally optimal sense. Furthermore, the proposed hybrid method and the delivered theorem are adjusted to tackle the digital time delay integration images and the Bayer mosaic images whose Bayer CFA structure has been widely used in modern commercial digital cameras. Based on the IMAX, Kodak, and screen content test image sets, the experimental results demonstrate that in high efficiency video coding, the proposed hybrid method has substantial quality improvement, in terms of the CPSNR quality, visual effect, CPSNR-bitrate trade-off, and Bjøntegaard delta PSNR performance, of the reconstructed RGB images when compared with existing chroma subsampling schemes.

In this paper, we propose a novel adaptive chroma subsampling-binding and luma-guided (ASBLG) chroma reconstruction method for screen content images (SCIs). After receiving the decoded luma and subsampled chroma image from the decoder, a fast winner-first voting strategy is proposed to identify the used chroma subsampling scheme prior to compression. Then, the decoded luma image is subsampled as the identified subsampling scheme was performed on the chroma image such that we are able to conclude an accurate correlation between the subsampled decoded luma image and the decoded subsampled chroma image. Accordingly, an adaptive sliding window-based and luma-guided chroma reconstruction method is proposed. The related computational complexity analysis is also provided. We take two quality metrics, the color peak signal-to-noise ratio (CPSNR) of the reconstructed chroma images and SCIs and the gradient-based structure similarity index (CGSS) of the reconstructed SCIs to evaluate the quality performance. Let the proposed chroma reconstruction method be denoted as `ASBLG'. Based on 26 typical test SCIs and 6 JCT-VC test screen content video sequences (SCVs), several experiments show that on average, the CPSNR gains of all the reconstructed UV images by 4:2:0(A)-ASBLG, SCIs by 4:2:0(MPEG-B)-ASBLG, and SCVs by 4:2:0(A)-ASBLG are 2.1, 1.87, and 1.87 dB, respectively, when compared with that of the other combinations. Specifically, in terms of CPSNR and CGSS, CSBILINEAR-ASBLG for the test SCIs and CSBICUBIC-ASBLG for the test SCVs outperform the existing state-of-the-art comparative combinations, where CSBILINEAR and CSBICUBIC denote the luma-aware based chroma subsampling schemes by Wang et al.