A selective update approach to matching pursuits video coding

This paper addresses an approach to video coding utilizing an iterative nonorthogonal expansion technique called ''matching pursuits'' (MP) in combination with a new algorithm for selecting an appropriate coding technique at each frame in a sequence, This decision algorithm is called ''selective update'' and is based on an estimate of the amount and type of motion occurring between coded frames in a video sequence, This paper demonstrates that the matching pursuits approach is most efficient for video coding when motion compensation results in prediction error which is well localized to the edges of moving objects, In the presence of global motion, such as panning and zooming, or in the presence of objects entering or leaving a scene, matching pursuits becomes less effective than orthogonal transform-based coding techniques like the block-based discrete cosine transform (DCT), The rate-distortion characteristics of matching pursuits and block-wise DCT coding are used to demonstrate how MP coding can be more efficient than block-wise DCT-based coding, When an appropriate combination of these nonorthogonal and orthogonal transforms are used for encoding a complete low bit-rate video sequence, improved overall compression efficiency can be achieved. Results are shown which demonstrate the effectiveness of a hybrid video codec based on this concept.