| has gloss | eng: Generalized lifting scheme was developed by and and published in Joel's PhD Thesis . It is based on classical lifting scheme and generalizes it breaking out a restriction hidden in the scheme structure. Classical lifting scheme has three kind of operations. # Lazy wavelet transform splits signal f_j[n] in two new signals: the odd samples signal denoted by f_j^o[n] and the even samples signal denoted by f_j^e[n]. # Prediction step its objective is compute a prediction for the odd samples, based on the even samples (or viceversa). This prediction is subtracted to the odd samples creating an error signal g_j+1}[n]. # Update step this step has not a clearly objective. In the case of classical Lifting, this is used in order to "prepare" the signal for the next prediction step. It uses the predicted odd samples g_j+1}[n] to prepare the even ones f_j^e[n] (or viceversa). This update is subtracted to even samples producing the signal denoted by f_j+1}[n]. |
