Abstract
图像纹理去除是指保留图像的语义结构并去除图像中的纹理和噪声部分,从而将纹理区域与结构特征划分开,是计算成像和图像分析的基础研究问题。近年来,在该领域中出现了许多优秀的算法,但它们在结构纹理的区分效果、纹理滤除的干净程度和算法运行的效率等方面仍存在一些问题和矛盾。鉴于此,提出一种基于区间梯度的滤波方法来去除图像纹理。首先,为简化先验模型的复杂度,将区间梯度的概念应用到结构提取模型中,实现了纹理与结构的二元化标记,为下一步单独对纹理区域进行滤波处理做准备。其次,针对复杂多变的纹理部分,将最值替换机制融入到联合双边滤波算法中,即在目标像素的邻域中选取颜色差异最大的像素作为颜色权重分布的中心点,使其在滤波过程中起主导作用。实验证明,所提方法能应用于多种纹理图像,可有效缓解强纹理去除与运算效率之间的矛盾,同时,因在达到相近纹理去除效果时所需迭代次数更少,其在同类滤波方法中取得了更好的边缘保持效果。
Image texture removal is a fundamental problem in image processing. It aims to decompose an image into texture patterns and structure features. Many filters have been proposed for removing image textures. However, these techniques suffer from some problems in balancing the performance among texture distinction, texture removal and time efficiency. In this paper, an interval gradient-based filter was proposed to remove image textures. First, to simplify the prior model, interval gradient is employed to extract the structure features. And the binary map that separates the structures from texture is achieved, which will be used as a guidance image when the filtering texture regions are processed. Then, to deal with complicated texture patterns, the shift smoothing technique is incorporated into joint bilateral filtering, and the pixel possessing the maximal color difference with the target pixel is selected as the center point for color weight distribution, so that it can dominate the filtering process. Experiments show that the proposed method can be applied to various types of texture images, achieving both effective texture removal and high time efficiency. Moreover, this method can better preserve the edge features attributing to fewer iteration times required for obtaining similar results of texture removal.
Image texture removal is a fundamental problem in image processing. It aims to decompose an image into texture patterns and structure features. Many filters have been proposed for removing image textures. However, these techniques suffer from some problems in balancing the performance among texture distinction, texture removal and time efficiency. In this paper, an interval gradient-based filter was proposed to remove image textures. First, to simplify the prior model, interval gradient is employed to extract the structure features. And the binary map that separates the structures from texture is achieved, which will be used as a guidance image when the filtering texture regions are processed. Then, to deal with complicated texture patterns, the shift smoothing technique is incorporated into joint bilateral filtering, and the pixel possessing the maximal color difference with the target pixel is selected as the center point for color weight distribution, so that it can dominate the filtering process. Experiments show that the proposed method can be applied to various types of texture images, achieving both effective texture removal and high time efficiency. Moreover, this method can better preserve the edge features attributing to fewer iteration times required for obtaining similar results of texture removal.
Translated title of the contribution | Interval gradient based joint bilateral filtering for image texture removal |
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Original language | Chinese (Simplified) |
Pages (from-to) | 29-34 |
Number of pages | 16 |
Journal | 计算机科学 = Computer Science |
Volume | 45 |
Issue number | 3 |
DOIs | |
Publication status | Published - 15 Mar 2018 |
Externally published | Yes |
Event | 第十届全国几何设计与计算学术会议 - 山东烟台, China Duration: 12 Aug 2017 → 14 Aug 2017 http://jsj.sdibt.edu.cn/gdc2017/ |
Bibliographical note
本文受国家自然科学基金 (61502137),香港研究资助局 (UGC/FDS11/E04/16),中国博士后基金 (2016M592047),香港教育大学院长研究基金 (FLASS/DRF/SFRS-1) 资助。Keywords
- 图像纹理去除
- 联合双边滤波
- 区间梯度
- 最值替换机制
- Image texture removal
- Joint bilateral filtering
- Interval gradient
- Shift smoothing technique