In this paper a sample-adaptive prediction technique is proposed to yield efficient coding performance in an intracoding for screen content video coding. The sample-based prediction is to reduce spatial redundancies in neighboring samples. To this aim, the proposed technique uses a weighted linear combination of neighboring samples and applies the robust optimization technique, namely, ridge estimation to derive the weights in a decoder side. The ridge estimation uses <i>L</i><sub>2</sub> norm based regularization term, and, thus the solution is more robust to high variance samples such as in sharp edges and high color contrasts exhibited in screen content videos. It is demonstrated with the experimental results that the proposed technique provides an improved coding gain as compared to the HEVC screen content video coding reference software.
3D-AVC being developed under Joint Collaborative Team on 3D Video Coding (JCT-3V) significantly
outperforms the Multiview Video Coding plus Depth (MVC+D) which simultaneously encodes texture views
and depth views with the multiview extension of H.264/AVC (MVC). However, when the 3D-AVC is
configured to support multiview compatibility in which texture views are decoded without depth information,
the coding performance becomes significantly degraded. The reason is that advanced coding tools incorporated
into the 3D-AVC do not perform well due to the lack of a disparity vector converted from the depth information.
In this paper, we propose a disparity vector derivation method utilizing only the information of texture views.
Motion information of neighboring blocks is used to determine a disparity vector for a macroblock, so that the
derived disparity vector is efficiently used for the coding tools in 3D-AVC. The proposed method significantly
improves a coding gain of the 3D-AVC in the multiview compatible mode about 20% BD-rate saving in the
coded views and 26% BD-rate saving in the synthesized views on average.