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Disparity estimation is a highly complex and time consuming process in multi-view video encoders. Since multiple views taken from a 2D camerea array need to be coded at every time instance, the complexity of the encoder plays an important role besides its rate-distortion performance. In previous papers we have introduced a new frame type called D frame that exploits the stron geometrical correspondence between views, thereby reducing the complexity of the encoder. By employing D frames instead of some of the P frames in the prediction structure, significant compexity gain can be achieved if the trhreshold value which is a keystone element to adjust the complexity at the cost of quality and/or bit-rate is selected wisely. In this work, a new adaptive method to calculate the threshold value automatically from existing information during the encoding process is presented. In this method, the threshold values are generated for each block of each D frame to increase the accuracy. The algorithm is applied to several image sets and 20.6% complexity gain is achieved using the automatically generated threshold values without compromising qaulity or bit-rate.

The introduction of HDTV asks for spatial up-conversion techniques enabling the display of standard resolution material. Recently, X. Li and M. Orchard proposed the 'New Edge-Directed Interpolation' (NEDI) algorithm for high quality up-scaling of natural images. We shall show that the method, although it generally behaves well, introduces annoying artifacts in fine-textured areas. Based on an analysis of these artifacts and taking advantage of the temporal correlation between video images, we propose an improved NEDI algorithm. In our evaluation, we compare the performance of the original and the improved NEDI method on a significant set of test images. We conclude from both subjective and objective measures that the proposed modifications improve the overall performance of NEDI.