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Structure-Aware Texture Filtering Based on Local Histogram Operator
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DOI：10.1109/ACCESS.2020.2977408.png)
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Abstract
En 中文
Smoothing the multi-scale textures with strong gradient while maintaining the weak structures is still a challenging work for the existing texture filtering methods. In this paper, we propose a variant of the bilateral filter to address this issue. Unlike the classical bilateral filter, which usually uses a fixed range kernel for texture filtering, the variant uses an adaptive range kernel, that is, if a pixel is located near a structure, the range kernel assigned to the pixel is small, otherwise, the range kernel is large. This mechanism ensures the preservation of sharp edges. In order to perform structure measurement, we propose a local histogram operator, which can identify structures from textures by comparing the difference in color distribution between the left and right half neighboring windows centered on the pixel of interest. In addition, after once bilateral filtering, instead of multiple iterations, a novel anisotropic filter is designed to remove residual textures, which can avoid edge blurring to some extent. Experimental results demonstrate the effectiveness of our method by comparing it with the state-of-the-art methods in preserving weak structures as well as suppressing textures with strong gradient or varying scales.
Keywords:
Smoothing methods
Kernel
Histograms
Image edge detection
Image color analysis
Filtering
Microsoft Windows
Texture filtering
bilateral filter
structure measurement
local histogram operator
adaptive range kernel
anisotropic filter
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