O. Pogrebnyak and P.M. Ramírez (Mexico)
Image Processing, Wavelets, Data Compression, Noise Suppression
A new algorithm of locally adaptive wavelet transform is presented. The algorithm implements the integer-to integer lifting scheme. It performs an adaptation of the wavelet function at the prediction stage to the local image data activity. The proposed algorithm is based on the generalized framework for the lifting scheme that permits to obtain easily different wavelet coefficients in the case of the ( N ~ , N ) lifting. It is proposed to perform the hard switching between (2, 4) and (4, 4) lifting filter outputs according to an estimate of the local data activity. When the data activity is high, i.e., in the vicinity of edges, the (4, 4) lifting is performed. Otherwise, in the plain areas, the (2, 4) decomposition coefficients are calculated. The calculations are rather simples, which permits the implementation of the designed algorithm in fixed point DSP processors. The proposed adaptive transform possesses the perfect restoration of the processed data and possesses better energy compactation in comparison to the non-adaptive lifting. The designed algorithm can be used for image compression and in the noise suppression applications.
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