正则化权值自适应的相对全变分图像平滑  

Adaptive regularization of the weighted relative total variation for image smoothing

作　　者：崔鹏[1] 梁皓涵 王志强 刘婷婷 Cui Peng;Liang Haohan;Wang Zhiqiang;Liu Tingting(School of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,China)

机构地区：[1]哈尔滨理工大学计算机科学与技术学院,哈尔滨150080

出　　处：《中国图象图形学报》2024年第12期3578-3594,共17页Journal of Image and Graphics

摘　　要：目的 针对目前已有的纹理结构滤波方法存在无法有效保证在滤除纹理的同时保持结构稳定的问题,提出一种正则化权值自适应的相对全变分图像平滑算法。方法 首先,提出一种具有纹理抑制和结构保持的多尺度区间圆形梯度算子,其中引入了定向各向异性结构度量框架,提高了纹理—结构间的区分度。随后,利用高斯混合模型和EM(expectation maximization)算法实现纹理层和结构层的分离。最后,根据纹理和结构之间的差异性,对相对全变分模型中的正则化项进行自适应设置,使之可以在纹理区域利用大权重的正则化权值进行纹理抑制;在结构区域利用小权重的正则化权值进行结构保持。结果 在视觉层面上,通过测试油画、十字绣、涂鸦、壁画和自然场景类型图像,并与已有的主流纹理结构滤波方法进行比较,本文算法不仅可以有效地抑制强梯度纹理,还可以保持弱梯度结构边缘的稳定;在定量度量方面,通过JPG格式图像压缩痕迹去除和高斯噪声图像平滑,并与相对全变分、滚动引导图像滤波、双边纹理滤波、尺度感知纹理滤波和L0梯度最小化等方法进行关于峰值信噪比(peak signal-tonoise ratio,PSNR)和结构相似度(structural similarity index,SSIM)指标的比较,本文方法均取得最大值。此外,本文方法将所生成的滤波结果应用于图像风格化、细节增强和超像素分割,效果具有一定改进和提升。结论 相较于已有的纹理结构滤波方法,本文方法在强梯度纹理抑制和精细结构保持方面更具优势,为后续图像处理奠定坚实的基础。Objective Texture shows different characteristics on different scales.On a smaller scale,the texture may appear more intricate and detailed,but on a larger scale,texture may present large structures and patterns.Therefore,texture patterns are complex and diverse and show various characteristics across patterns.For example,structural texture has clear geometric shape and arrangement,natural texture has randomness and complexity,and abstract texture presents a combination of different colors,lines,and patterns.While the human visual system can effectively distinguish an ordered structure from a disordered one,computers are generally unable to do so.Texture filtering is a basic and important tool in the fields of computer vision and computer graphics whose main purpose is to filter out unnecessary texture details and maintain the stability of the core structure.The mainstream texture filtering methods are mainly divided into local-and global-based methods.However,the existing texture filtering methods do not effectively guarantee the structural stability while filtering the texture.To address this problem,we propose an adaptive regularization of the weighted relative total variation for image smoothing algorithm.Method The main idea of this algorithm is to obtain a structure measure amplitude image with high texture structure discrimination and then use the relative total variation model to smooth this image according to the difference between the texture and structure.Our method implements texture filtering and structure preservation in three steps.First,we propose a multi-scale interval circular gradient operator that can effectively distinguish texture from structure.By inputting the intensity change information of the interval gradient in the horizontal and vertical directions(captured by the interval circular gradient operator) into the frame of directional anisotropic structure measurement(DASM),we generate a structure measure amplitude image with high contrast.In each iteration,we constantly adjust the scale

关 键 词：图像平滑 纹理滤波 相对全变分 多尺度 正则项自适应 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]