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Recursive Wavelet Filters for Video Coding

机译:用于视频编码的递归小波滤波器

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Recursive wavelet filters and an alternative algorithm for implementing wavelet transform are presented in this paper. The recursive filters use previously calculated (past) wavelet coefficients as inputs to calculate the current wavelet coefficient, and provide the same transform results as convolutional FIR and lifting wavelet filters. The coefficients of the recursive filters are derived from those of conventional FIR wavelet filters. The wavelet transform with recursive filters requires a smaller amount of memory and is easy to implement in hardware. Another important advantage of the recursive filters is that perfect reconstruction can be easily achieved using recursive wavelet filters if a sequence of pixels to be transformed is extended by boundary pixel repetition. Boundary pixel repetition can be more efficient than the widely used method of symmetric extension for image and video coding.
机译:提出了递归小波滤波器和实现小波变换的替代算法。递归滤波器使用先前计算的(过去)小波系数作为输入来计算当前小波系数,并提供与卷积FIR和提升小波滤波器相同的变换结果。递归滤波器的系数是从常规FIR小波滤波器的系数中得出的。具有递归滤波器的小波变换需要较少的内存,并且易于在硬件中实现。递归滤波器的另一个重要优点是,如果要转换的像素序列通过边界像素重复扩展,则使用递归小波滤波器可以轻松实现完美的重构。边界像素重复比图像和视频编码中广泛使用的对称扩展方法更有效。

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