Related Reductive Texture Decomposition via Bilateral Kernel Regression

It is ubiquitous that meaningful structures are appear over textured surfaces. Extracting them under the complication of texture patterns is very challenging, but of great practical importance. Consequently, we have proposed a novel structure-aware filter via bilateral kernel regression with a variational structure-kernel descriptor which can extract main structures from textures through variational structure-kernel descriptor and incorporate its results into the bilateral kernel regression:we first apply the related reductive texture decomposition to construct the structure-kernel descriptor. Then, we incorporate the descriptor into the bilateral kernel regression to achieve an expected structure-preserving output. Algorithmically, we propose a numerically stable approximation iterative procedure to achieve effective implementation. At last, some experimental results are presented to demonstrate that our approach leads to better or comparable performance and is effect in some applications, such as HDR, super-pixel segmentation and so on.