Adaptive multiresolution image coding with matching and basis pursuits

There has been a growing interest in representation and compression of signals by using dictionaries of basis functions other than the traditional dictionary of sinusoids. These new set of dictionaries include cosine packets, chirplets, Gabor functions, wavelets, and wavelet packets. In this paper matching pursuit and basis pursuit with finite dictionaries of convolutional splines are used for adaptive multiresolution image compression. At the cost of computational complexity these algorithms outperform the DCT based JPEG both in terms of PSNR and subjective image quality at lower bit rates