Abstract:
We present a new algorithm for matching pursuit (MP) dictionary design. This technique uses existing vectorquantization (VQ) design techniques and an inner-product based distortion measure to learn functions from a set of training patterns. While this scheme can be applied to many MP applications, we focus on motion compensated video coding. Given a set of training sequences, data is extracted from the high energy packets of the motion compensated frames. Dictionaries with different regions of support are trained, pruned, and finally evaluated on MPEG test sequences. We find that for high bit-rate QCIF sequences we can achieve improvements of up to 0.66 dB with respect to conventional MP with separable Gabor functions. Index Terms video coding, matching pursuit, dictionary design, vector-quantization
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