One of tasks of image filter is to preserve strong edge structure and smooth textures in the given image. Recently, many approaches have been proposed to accomplish this challenging task. In this paper, we propose a scale adaptive structure tensor based rolling trilateral filter to smooth detailed small textures while preserving prominent structures. The proposed method first estimates scale at each pixel using a structure measure; then computes the eigenvalues and eigenvectors of structure tensor constructed from gradient at each pixel. The trilateral filter includes anisotropic weight in spatial space, the Gaussian weight in range space and the Gaussian weight of inner product of eigenvectors in gradient space. Results of experiments conducted on many natural images demonstrate that the proposed filter performs well.
Filtering image by eliminating irrelevant details as could as possible while preserving structure edge and corner becomes very important in the fields such as image processing and computer vision etc. In this paper, we present an Anisotropic Rolling Filter (ARF) for smoothing image while preserving important structure edge and corner. The proposed filter implements an extended cross bilateral filter, in which the range weights are updated in an iterative manner, while the spatial Gaussian weights are computed in anisotropic directions instead of isotropic directions. The anisotropic directions are computed based on structure tensors which are calculated at each pixel to determine structure orientations. Compared with the original rolling guidance filter, it is found that the proposed anisotropic rolling filter has stronger smoothing and structure preserving ability.
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