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Log-transform Weighted Total Variation for Image Smoothing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 124 - Number 2 |
| Year of Publication: 2015 |
| Authors: Qiegen Liu, Li Zhu, Jianhua Wu |
10.5120/ijca2015905411
|
Qiegen Liu, Li Zhu, Jianhua Wu . Log-transform Weighted Total Variation for Image Smoothing. International Journal of Computer Applications. 124, 2 ( August 2015), 35-40. DOI=10.5120/ijca2015905411
Abstract
Since the input image in computer vision and graphics containing various texture/structure patterns provides rich visual information, how to properly decompose them is a challenging problem. Recent developments in high-contrast detail smoothing show that how they define edges and how this prior information guides smoothing are two key points. In this paper, we present a novel Log-transform weighted total variation (LWTV) method, which employs the signed gradient summation of Log-transform pixels at neighbor window as data-fidelity weight. Specifically, LWTV substantially improves the decomposition for the regions with faint pixel-boundary and alleviates the drawback of slightly blurry. Experimental results demonstrate that the proposed method has appearance performance on image with abundant uniform textural details.
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