A lifting based system for optimal image compression in the wavelet domain

Wavelets are used in most of the recent image compression standards, because they provide scalability, multi-resolution, and energy concentration. Most of these wavelet image coders employ bi-orthogonal filters. This provides the advantages of selective frequency localization and Perfect Reconstruction (PR), compared to classical orthogonal filters. Bi-orthogonal filters also obviate the need for any phase compensation in the pyramidal filter structure. Lifting has emerged as a powerful method for implementing bi-orthogonal wavelet filters. It exploits the similarity of the filter coefficients between the low pass and high pass filters to provide a higher speed of execution, compared to conventional convolution-based coders. In this paper, we propose a novel lifting-based system that achieves better compression than existing wavelet kernels. The proposed lifting-based system uses bi-orthogonal filters in its architecture, and can operate in the JPEG2000 framework. In the proposed system, the coefficients of either the low-pass or high-pass filter can be modified, without changing the coefficients of the other filter. This is done in a manner that enhances compression while preserving the perfect reconstruction (PR) condition, and increasing the regularity of the modified pair of filters. Extensive simulations have been performed in the JPEG2000 domain to compare the efficiency of our kernels to the lifting wavelet kernels provided by the JPEG2000 standard