Reducing aliasing in wavelets based downsampling for improved resolution scalability

In wavelets based coding applications, resolution scalability is achieved by retaining the low pass signal subband corresponds to the required resolution and discarding other high pass wavelet subbands. Aliasing is a common problem present in such downsampling. In this paper a novel technique for improving the low pass filter for improved downsampling is presented. This method uses an extra update step followed by P+U lifting scheme. The preprocessing update step is chosen as the dual update step associated with the wavelet. The spatially adaptive low pass (SALP) filtering concept is used for the second update step, leading to an overall low pass filter whose size adapts to the underlying signal content. The filter choices for the second update step is recovered at the decoder without any bookkeeping. Results using the 2D 5/3 wavelet with the extra pre-processing update step show improvements over conventional wavelets.