In general, it is necessary for Multi-view Video Coding (MVC) methods to compress multi-view videos efficiently and
have a property of view-scalability in order to decode arbitrary views according to any viewer's interests. Much research
has been done on MVC methods, with the goal of increasing coding efficiency. Although these previous methods have
considered the property of view-scalability, a lot of coding bits and delays were necessary to decode arbitrary views. In
this paper, we propose an MVC method based on image stitching. We generated a stitched reference and encoded multiview
sequences using disparity-compensated method. The proposed method is able to reduce delays during the decoding
stage. Experimental results show that the proposed MVC method increased the PSNR by 1.5~2.0dB and saved 10% of
the coding bits compared to simulcast coding.
This paper presents an efficient joint disparity-motion estimation algorithm and fast estimation scheme for stereo sequence CODEC. In stereo sequences, frames from one camera view (usually the left) are defined as the base layer, and frames from the other one as the enhancement layer. The enhancement-from-base-layer prediction then turns out as a disparity-compensated prediction instead of a motion-compensated prediction. Although the disparity-compensated prediction fails, it is still possible to achieve compression by motion-compensated prediction with the same channel. At the same time, the base layer represents a monoscopic sequence. Joint disparity-motion estimation can increase coding efficiency and reduce complexity of stereo CODEC using relationship between disparity and motion fields. The disparity vectors are estimated by using the left and right motion vectors and the previous disparity vectors in each time frame. In order to obtain more accurate disparity vectors, we include spatial prediction process after joint estimation. From joint estimation and spatial prediction, we can obtain accurate disparity vectors and then increase coding efficiency. Moreover, we proposed fast motion estimation technique which utilizes correlation for motion vectors of neighboring blocks. We confirmed PSNR of the proposed method increases by 0.5~1.5dB compared to the conventional methods from simulation results. At the same time, the processing time is reduced by almost 1/10.