A new structure of spline wavelet transform based on adaptive directional lifting for efficient image coding

We present in this paper a modified structure of a polynomial spline wavelet transform based on adaptive directional lifting for image compression. The proposed method not only uses the polynomial splines as a tool for the construction of the appropriate filters seeing its efficiency as compared to other filters like the biorthogonal 9/7, but also adapts far better to the image-orientation features by carrying out a lifting-based prediction in local windows in the direction of high pixel correlation. The main purpose of this article is then to integrate the coefficients calculated by the best spline filter order into the adaptive directional lifting. The new method is designed to further reduce the magnitude of the high-frequency wavelet coefficients and preserve the detailed information of the original images more effectively. The numerical results demonstrate the efficiency of the proposed approach over the traditional lifting-based spline wavelet transform and the adaptive directional lifting with respect to both objective and subjective criteria for image compression applications.