Bolun Cai, Xiaofen Xing, Xiangmin Xu
This paper presents a novel edge/structure-preserving image smoothing via relativity-of-Gaussian. As a simple local regularization, it performs the local analysis of scale features and globally optimizes its results into a piecewise smooth. The central idea to ensure proper texture smoothing is based on cross-scale relative that captures the weak textures from the most prominent edges/structures. Our method outperforms the previous methods in removing the detail information while preserving main image content.
If you use these codes in your research, please cite:
@article{cai2017rog,
author = {Bolun Cai, Xiaofen Xing and Xiangmin Xu},
title={Edge/Structure Preserving Smoothing via Relativity-of-Gaussian},
booktitle={IEEE International Conference on Image Processing (ICIP)},
year={2017}
}
Download the code and test images
git clone https://github.com/caibolun/RoG.git
Smooth the image with edge/structure Preserving by simply typing in Matlab.
run('demo.m')
Detail Enhancement (Link)
As a nonlinear edge-preserving image smoothing (K = 1), our method can be used for detail enhancement via base and detail layer decomposition.
run('detail_example\demo.m')
Structure Extraction (Link)
As a nonlinear structure-preserving image smoothing (K > 1), we apply our method for structure-texture separation.
run('struct_example\demo.m')
HDR Tone Mapping (Link)
One of the challenges in image processing is the rendering of an HDR scene on a conventional LDR display. RoG smoothing is easily harnessed to perform tone mapping of HDR images.
run('hdr_example\demo.m')
