The novel 'Basis Picking' algorithm is applied to select dictionaries of 1D basis functions for coding of image data by Matching Pursuits. For both motion compensated residual images and normal still images, bases are picked with a hybrid Wavelet/Matching Pursuits image codec using 1D scanning. By successively adding bases one at a time from a set of 1289 candidates according to their ranked signal to residual ratio (SRR) performance, effective codebooks are constructed. These outperform traditional selection by ranked frequency of use from the same candidate bases over a range of compressions of both residuals and still images. This holds for both the training sets used for picking and other test images. Picked bases are also capable of good quality compression of still images, which was not previously thought to be feasible by matching pursuits.
['Donald M. Monro']
Basis picking for matching pursuits image coding