MLC: a novel image coder based on multitree local cosine dictionaries

We build a multitree dictionary of local cosine bases and develop a novel image coder that extracts the best basis in such a dictionary with respect to a rate-distortion cost. This dictionary is much larger than standard quadtree-based dictionaries, and therefore, our algorithm needs more overhead bits to encode the basis selection. Despite this, we show that the resulting algorithm outperforms an existing quadtree local cosine image compression algorithm. We also show that our multitree local cosine coder outperforms both SPIHT and a multitree block-DCT method previously developed by us, on several textured images.