An Efficient Structure-Aware Bilateral Texture Filtering for Image Smoothing

2016 ◽  
Vol 35 (7) ◽  
pp. 57-66 ◽  
Author(s):  
Ting-Hao Lin ◽  
Der-Lor Way ◽  
Zen-Chung Shih ◽  
Wen-Kai Tai ◽  
Chin-Chen Chang
Keyword(s):  
Image Smoothing ◽  
Texture Filtering

Structure-preserving texture filtering for adaptive image smoothing

2018 ◽  
Vol 45 ◽  
pp. 17-23 ◽  
Author(s):  
Chengfang Song ◽  
Chunxia Xiao ◽  
Xuefei Li ◽  
Jing Li ◽  
Haigang Sui
Keyword(s):  
Image Smoothing ◽  
Structure Preserving ◽  
Texture Filtering

scholarly journals Image smoothing based on global sparsity decomposition and a variable parameter

2021 ◽  
Author(s):  
Xiang Ma ◽  
Xuemei Li ◽  
Yuanfeng Zhou ◽  
Caiming Zhang
Keyword(s):  
Removal Rate ◽  
Variable Parameter ◽  
Smoothing Parameter ◽  
Smoothing Effect ◽  
Image Smoothing ◽  
Sparse Decomposition ◽  
Alternating Direction ◽  
Texture Removal ◽  
Ideal Algorithm ◽  
Better Than

AbstractSmoothing images, especially with rich texture, is an important problem in computer vision. Obtaining an ideal result is difficult due to complexity, irregularity, and anisotropicity of the texture. Besides, some properties are shared by the texture and the structure in an image. It is a hard compromise to retain structure and simultaneously remove texture. To create an ideal algorithm for image smoothing, we face three problems. For images with rich textures, the smoothing effect should be enhanced. We should overcome inconsistency of smoothing results in different parts of the image. It is necessary to create a method to evaluate the smoothing effect. We apply texture pre-removal based on global sparse decomposition with a variable smoothing parameter to solve the first two problems. A parametric surface constructed by an improved Bessel method is used to determine the smoothing parameter. Three evaluation measures: edge integrity rate, texture removal rate, and gradient value distribution are proposed to cope with the third problem. We use the alternating direction method of multipliers to complete the whole algorithm and obtain the results. Experiments show that our algorithm is better than existing algorithms both visually and quantitatively. We also demonstrate our method’s ability in other applications such as clip-art compression artifact removal and content-aware image manipulation.

Image smoothing based on histogram equalized content-aware patches and direction-constrained sparse gradients

2021 ◽  
Vol 183 ◽  
pp. 108037
Author(s):  
Yepeng Liu ◽  
Fan Zhang ◽  
Yongxia Zhang ◽  
Xuemei Li ◽  
Caiming Zhang
Keyword(s):  
Image Smoothing ◽  
Content Aware

scholarly journals A Novel Image Smoothing Filter Using Membership Function

2007 ◽  
Vol 20 (4) ◽  
pp. 381-392 ◽  
Author(s):  
Tzong-Jer Chen ◽  
Keh-Shih Chuang ◽  
Sharon Chen ◽  
Jeng-Chang Lu ◽  
Ya-Hui Shiao
Keyword(s):  
Membership Function ◽  
Image Smoothing ◽  
Smoothing Filter

A method to design filters for image smoothing

1992 ◽  
Vol 13 (7) ◽  
pp. 509-515
Author(s):  
G.P. He ◽  
K. Kraus
Keyword(s):  
Image Smoothing

Dense range image smoothing using adaptive regularization

2000 ◽  
Author(s):  
Yiyong Sun ◽  
Joon-Ki Paik ◽  
J.R. Price ◽  
M.A. Abidi
Keyword(s):  
Range Image ◽  
Image Smoothing ◽  
Adaptive Regularization ◽  
Dense Range

Multiresolution Adaptive Image Smoothing

1994 ◽  
Vol 56 (2) ◽  
pp. 140-148 ◽  
Author(s):  
P. Meer ◽  
R.H. Park ◽  
K.J. Cho
Keyword(s):  
Image Smoothing
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