结合纹理梯度抑制与L_0梯度最小化的纹理滤波  

Texture filtering by using texture gradient suppression and L_0 gradient minimization

作　　者：邵欢 刘春晓[1] Shao Huan;Liu Chunxiao(School of Computer Science ＆ Information Engineering,Zhejiang Gongshang University,Hangzhou 310018,China)

机构地区：[1]浙江工商大学计算机与信息工程学院,杭州310018

出　　处：《中国图象图形学报》2018年第11期1666-1675,共10页Journal of Image and Graphics

基　　金：国家自然科学基金项目(61379075;61472363;U1609215);浙江省自然科学基金项目(LY14F020004);国家科技支撑计划项目(2014BAK14B01);浙江省公益性技术应用研究计划项目(2015C33071);浙江工商大学青年人才基金项目(QZ13-9);浙江省智能交通工程技术研究中心开放课题(2015ERCITZJ-KF1)~~

摘　　要：目的纹理滤波是计算机视觉领域的一个基础应用工具,其目标是抑制图像中不必要的纹理细节和保持图像的主要结构。目前已有的纹理滤波方法多存在强梯度纹理无法被抑制或结构丢失的问题,为此提出一种结合纹理梯度抑制与L_0梯度最小化的纹理滤波算法。方法首先,提出一种能够区分结构/纹理像素的方向性区间梯度算子,其中采取了局部对比度拉伸和尺度自适应策略,提升了弱梯度结构像素的识别能力。随后,利用区间梯度幅值对原始图像梯度进行抑制,并用抑制后的图像梯度进行图像重建,获得纹理像素梯度小于结构像素梯度的纹理抑制图像。最后,考虑到纹理梯度抑制时会对结构像素的梯度产生一定的衰减作用,本文采用具有梯度提升作用的L_0梯度最小化方法对纹理抑制图像进行滤波,得到纹理抑制结构保持的纹理滤波图像。结果通过测试马赛克和自然风景等不同类型的图片,并与L_0梯度最小化、滚动引导图像滤波、相对总变分、共现滤波等方法相比较,本文算法能够在抑制强梯度纹理的情况下对图像的主要结构得以保持,并且具有良好的普适性和鲁棒性。同时本文将纹理滤波应用于图像的边缘检测和细节增强,取得了不错的效果提升。结论本文算法在兼顾强梯度纹理的抑制和结构的保持方面已超越已有的方法,对于图像的目标识别、图像融合、边缘检测等易受强梯度纹理干扰的技术领域,具有较大的应用潜力。Objective Texture is a repetitive pattern with high pixel values. Many natural images and works of art include textures such as cross-stitch and mosaic. In many cases, the visual system of individuals ignores the texture pattern and fo- cuses on the main structure of an image. Texture filtering is a basic tool in the computer graphics and image processing fields ; the goal of which is to suppress unnecessary texture details and maintain the salient structure in the image. In recent years, various texture filtering methods, which are mainly divided into global- and local-based filtering methods, have been proposed. Most of the existing texture filtering methods handle the small gradient texture images. However, handling thestrong gradient texture and losing part of the structure is difficult. To solve this problem, we propose a texture filtering method by using texture gradient suppression and Lo gradient minimization to suppress texture and maintain the structure. Method The main idea of this algorithm is to obtain an input image with strong gradient texture suppression and then attain the smooth filtering results through the traditional texture filtering method, which uses L0 gradient minimization. Our method involves three steps to achieve the goal of image filtering. First, we improve the interval gradient operator, which has the capability to distinguish texture and structure pixels. We propose a directional interval gradient operator to increase the gra- dient amplitude by finding the main direction of the structure. We use a local contrast stretching strategy when calculating the direction interval gradient to improve the recognition capability of the weak gradient structure because the pixel gradient value of the weak structure area becomes smaller than the gradient value of the strong gradient texture. The directional in- terval gradient affects the texture suppression; thus, selecting a computational scale is particularly important. A scale adap- tive strategy, which automatically selects the optimal sca

关 键 词：纹理滤波 L0梯度最小化 强梯度纹理 结构保持 纹理抑制 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]