A joint design of dictionary approximation and maximum atom extraction for fast matching pursuit
We propose a new systematic approach to reduce matching pursuit (MP) encoder complexity. MP codecs are asymmetric as decoder complexity is low while the encoder complexity is extremely high. An MP encoder contains three components: the inner products, maximum atom extraction and atom encoding. We propose a new approach which combines the first two components using eigen-dictionary approximation and tree-based vector quantization (VQ). The advantages of this are a simpler design and a slower growth of computational costs as the target dictionary becomes large than traditional approaches. By varying the approximation accuracy, our algorithm can provide the trade-off between coding performance and speed-up of the MP encoder.