Enhanced MultiResolution Analysis for MultiDimensional Data Utilizing Line Filtering Techniques

In this article we introduce line Smoothness-Increasing Accuracy-Conserving Multi-Resolution Analysis. This is a procedure for exploiting convolution kernel post-processors obtaining more accurate multidimensional multiresolution analysis in terms of error reduction. filtering-projection tool allows the transition data between different resolutions while simultaneously decreasing errors fine grid approximation. It specifically defining detail multiwavelet coefficients when translating coarse onto finer meshes. These are usually not defined such cases. We show how to analytically evaluate resulting convolutions and express filtered approximation new basis. done by combining filtering with projection operators that allow computational implementation scale procedure. Further, can be applied piecewise constant approximations functions, as it provides demonstrate effectiveness technique two three dimensions.