Optimal weighted model-based bit allocation for quincunx sampled images

In this paper we address the problem of quincunx sampled images compression. Our objective is to define an efficient bit allocation method adapted to quincunx sampled images. We first estimate the subband optimal weightings for a global distortion estimation. These weightings are derived from the filters used to perform the quincunx wavelet transform. Then, we use our weightings in a model-based bit allocation procedure. Our method uses generalized Gaussians to approximate the probability density function of the wavelet coefficients in each subband. The bit allocation method which is proposed provides both low complexity and high performance.