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.

中文翻译：

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基于自适应方向提升的样条小波变换新结构实现高效图像编码

我们在本文中提出了一种基于自适应方向提升的多项式样条小波变换的改进结构，用于图像压缩。所提出的方法不仅使用多项式样条作为构建适当滤波器的工具，与其他滤波器（如双正交 9/7）相比，它的效率更高，而且通过执行提升更适应图像方向特征-基于高像素相关方向的局部窗口预测。然后本文的主要目的是将最佳样条滤波器阶数计算的系数整合到自适应方向提升中。新方法旨在进一步降低高频小波系数的幅度，更有效地保留原始图像的详细信息。