Improved video coding efficiency exploiting tree-based pixelwise coding dependencies

In a conventional hybrid video coding scheme, the choice of encoding parameters (motion vectors, quantization parameters, etc.) is carried out by optimizing frame by frame the output distortion for a given rate budget. While it is well known that motion estimation naturally induces a chain of dependencies among pixels, this is usually not explicitly exploited in the coding process in order to improve overall coding efficiency. Specifically, when considering a group of pictures with an IPPP... structure, each pixel of the first frame can be thought of as the root of a tree whose children are the pixels of the subsequent frames predicted by it. In this work, we demonstrate the advantages of such a representation by showing that, in some situations, the best motion vector is not the one that minimizes the energy of the prediction residual, but the one that produces a better tree structure, e.g., one that can be globally more favorable from a rate-distortion perspective. In this new structure, pixel with a larger descendance are allocated extra rate to produce higher quality predictors. As a proof of concept, we verify this assertion by assigning the quantization parameter in a video sequence in such a way that pixels with a larger number of descendants are coded with a higher quality. In this way we are able to improve RD performance by nearly 1 dB. Our preliminary results suggest that a deeper understanding of the temporal dependencies can potentially lead to substantial gains in coding performance.