Efficient disparity vector coding for multiview sequences

Abstract A multiview sequence codec with view scalability was described in a previous paper. To enhance the performance of this codec, an efficient disparity vector coding method for multiview sequences is proposed herein. For higher coding efficiency, we encode the differential vectors acquired by subtracting the original vectors from the predicted ones. To enhance the performance of disparity vector coding, it is essential to predict the disparity vectors accurately. The prediction by this proposed method utilizes the correlation among the multiview images, while conventional methods exploit the correlation among the causal blocks. Experiments were performed for three different 5 view sequences. We were able to confirm that the proposed method predicts disparity vectors accurately by comparing the entropy and the mean absolute values for differential vectors with conventional methods. Its performance is superior to vector coding methods used in MPEG-4 which uses only a spatial correlation. The proposed method increases the coding efficiency by a factor of 30–45% while preserving image quality.